METHOD AND APPARATUS FOR CREATING ENCODED DATA AND USE OF SAME FOR IDENTITY VERIFICATION

§101 §102 §103 §DOUBLEPATENT

DETAILED ACTION Claim 1,2,3,4,5,6,7,8 objected to because of the following informalities: Claims 1-8 and 9-13 and 14-18 provisionally rejected on the ground of nonstatutory double patenting as being unpatentable over claim 1-20 of copending Application No. US 2026/0024378 A1 in view of Tussy (US 2021/0011986 A1). Claim(s) 1,2,3,4,5,6,7,8 and 9,10,11,12,13 and 14,15,16,17,18 is/are rejected under 35 U.S.C. 103 as being unpatentable over GRIESER et al. (EP 3 889 922 A1) with SEARCH machine translation plus SEARCH machine translation II in view of YOSHIDA (WO 2019/132047 A1) with SEARCH machine translation and Tussy (US 2021/0011986 A1). Response to Amendment The amendment was received 8/6/2026. Claims 1-18 pending. Claim Objections Claim 1,2,3,4,5,6,7,8 objected to because of the following informalities: Claim 1, line 6’s: “the face derived face feature vector data” is objected for not being consistent1 with claim 1, lines 5,6’s: “a face derived feature vector data”. Claim 1, line 8’s “the graphic” is objected for missing the corresponding article “a” as in “a graphic”. Claim 1, line 8’s “the graphic” is interpreted as:–[[the]] a graphic--. Claim 1, line 8’s “the item” is objected for missing the corresponding article “a” as in “an item”. Claim 1, line 8’s “the item” is interpreted as:–[[the]] an item--. Thus claims 2,3,4,5,6,7,8 objected. Claim 7’s “the threshold” objected for truncating claim 1, line 15’s “a first threshold value” (see applicant’s fig. 12B, reproduced below, that shows a first-something, second-something and third-something regardless of ordinal ordering). Claim 7’s “the threshold” is interpreted as being regardless of order: “the n-th threshold value”. Appropriate correction is required. PNG media_image1.png 1151 772 media_image1.png Greyscale 35 USC § 101-Positive Statement 35 U.S.C. 101 reads as follows: Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title. Claims 1-18 not rejected under 35 U.S.C. 101 because the claimed invention is directed to improving a technical field of security more specifically face matching verification systems, applicant’s disclosure: US 2024/0346852 A1: [0001] without significantly more. The claim(s) recite(s) a mental process (comparing) (step 2A:prong 2). This judicial exception is not not integrated into a practical application because additional elements (“cannot be reverse processed”, claim 1 representative) reflect the improvement in applicant’s disclosure such as at [0386]) (step 2A:prong 2). The claim(s) does/do not not include additional elements (“cannot be reverse processed”, claim 1 representative) that are sufficient to amount to significantly more than the judicial exception because additional elements (“cannot be reverse processed”, claim 1 representative) is significantly more than the known, conventional (practical) and routine “proprietary2 encryption schemes” [0389] (step 2B). Double Patenting The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the claims at issue are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); and In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969). A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on a nonstatutory double patenting ground provided the reference application or patent either is shown to be commonly owned with this application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP §§ 706.02(l)(1) - 706.02(l)(3) for applications not subject to examination under the first inventor to file provisions of the AIA . A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b). The USPTO Internet website contains terminal disclaimer forms which may be used. Please visit www.uspto.gov/forms/. The filing date of the application in which the form is filed determines what form (e.g., PTO/SB/25, PTO/SB/26, PTO/AIA /25, or PTO/AIA /26) should be used. A web-based eTerminal Disclaimer may be filled out completely online using web-screens. An eTerminal Disclaimer that meets all requirements is auto-processed and approved immediately upon submission. For more information about eTerminal Disclaimers, refer to http://www.uspto.gov/patents/process/file/efs/guidance/eTD-info-I.jsp. Claims 1-8 and 9-13 and 14-18 provisionally rejected on the ground of nonstatutory double patenting as being unpatentable over claim 1-20 of copending Application No. US 2026/0024378 A1 in view of Tussy (US 2021/0011986 A1). This is a provisional nonstatutory double patenting rejection: PNG media_image2.png 654 103 media_image2.png Greyscale Regarding the provisional nonstatutory double patenting rejection of Claims 1-8 and 9-13 and 14-18: The following table illustrates the correspondence between the claimed limitation of 1-18 of the current application and the claimed limitation of 1–20 of US 2026/0024378 A1 (US Patent app): 18/627,383 (instant app) US 2026/0024378 A1 (US Patent app) 1. (currently amended) A method of validating a person's identity comprising: capturing one or more images of the person's face with a digital camera, wherein the person is live and physically present in front of the camera; processing the one or more images of the person's face to generate a face derived feature vector data, the face derived face feature vector data representing the person's face but not capable of being reverse processed to generate the image of the person's face from which it was derived ; capturing one or more images of the graphic on the item with the camera; processing one or more of the images of the graphic code to extract graphic derived face feature vector data that is stored inside the graphic code3 such that the graphic derived face feature vector data represents the person's face but cannot be reverse processed to generate the image of the person's face from which it was derived; comparing the face derived face feature vector data to the graphic derived face feature vector data to develop a similarity value; and comparing the similarity value to a first threshold value, and based on the comparing to the first threshold value , generating a validation indicator that represents the likelihood that the graphic is associated with the person. 2. (original) The method of claim 1, wherein the item is one of the following: driver's license, identification card, passport, diploma, education transcript, credit card, debit card, airline ticket, shipping label, event ticket, voting ballot, or title of ownership. 3. (currently amended) The method of claim 1 wherein the face derived face feature vector data comprises a string of alpha and numeric values that is 4. (original) The method of claim 1 wherein the item includes a picture of the person. 5. (currently amended) The method of claim 4 wherein the method further comprises: capturing, with the camera, one or more photographic images of a photograph of the person's face that is on the item; processing the one or more photo images to generate a photograph derived face feature vector data which represents the person’s face but is not capable of being reverse processed to generate an image of the person shown in the photograph; comparing the photograph derived face feature vector data to the face derived face feature vector data, the graphic derived face feature vector data, or both to develop a second similarity value; comparing the second similarity value to the first threshold value or a second threshold value, and based on the comparing, generating a second validation indicator. 6. (currently amended) The method of claim 1 wherein the face derived face feature vector data is created by a trusted entity from a trusted face photo of the person. 7. (currently amended) The method of claim 1 wherein the similarity value must be the same as or greater than the threshold value for the person’s identity to be validated4. 8. (currently amended) The method of claim 1, further comprising transmitting the face derived face feature vector data, the graphic derived face feature vector data, or both to a trusted entity and the trusted entity comparing the face derived face feature vector data, the graphic derived face feature vector data, or both to a trusted face feature vector stored at the trusted entity. 9.5 (currently amended) A system to validate a person’s identity using a graphic6 , the system comprising: a camera configured to~ capture at least one facial image of the person, wherein the person is live and physically present in front of the camera7; and capture a graphic image of the graphic located on the document; a processor configured to execute machine readable code stored in a non-transitory state on a memory; the memory storing the machine readable code in the non-transitory state, the machine readable code configured to: process the at least one facial image to generate a face derived face vector code, the face derived face vector code representing the person’s face, but not capable of being reverse processed to generate a face image of the person from which it was derived; process the graphic image to generate a graphic extracted face vector code, the graphic extracted face vector code representing the person’s face , but not capable of being reverse processed to generate an image of the person from which it was derived; comparing the face derived face vector code to the graphic extracted face vector code to develop a similarity value {, such that the face derived code and the graphic extracted code represent the person’s face}8; {{comparing the similarity value to a first threshold value, and based on the comparing to the first threshold value, generating a validation indicator that represents the likelihood that the graphic extracted face vector codeis associated with the person}}910. 9.11 (currently amended) A system to validate a person’s identity using a graphic12 , the system comprising: a camera configured to capture at least one facial image of the person , wherein the person is live and physically present in front of the camera13; and {capture a graphic image of the graphic located on the document}14; a processor configured to execute machine readable code stored in a non-transitory state on a memory; the memory storing the machine readable code in the non-transitory state, the machine readable code configured to: process the at least one facial image to generate a face derived face vector code, the face derived face vector code representing the person’s face, but not capable of being reverse processed to generate a face image of the person from which it was derived; process the graphic image to generate a graphic extracted face vector code , the graphic extracted face vector code representing the person’s face, but not capable of being reverse processed to generate an image of the person from which it was derived; comparing the face derived face vector code to the graphic extracted face vector code to develop a similarity value {{, such that the face derived code and the graphic extracted code represent the person’s face}}15 ; comparing the similarity value to a first threshold value, and based on the comparing to the first threshold value , generating a validation indicator that represents the likelihood that the graphic extracted face vector code is associated with the person. 10. (original) The system of claim 9 wherein the document comprises one of the following: driver’s license, title of ownership, school transcript, transaction check, identification card, event ticket or voting ballot. 11. (currently amended) The system of claim 9 wherein the face derived face vector code and the {{{graphic extracted}}}16 face vector code comprise a string of alpha-numeric values and {{{the graphic extracted}}} face vector code is stored in the graphic. 12.17 (currently amended) The system of claim 9 wherein the machine readable code is further configured to: capture one or more images of a face photograph , asserted to be the person , that is located on the document; process the one or more images of the face photograph to generate a face photograph derived face vector code which is not capable of being reverse processed to generate an image of the person; comparing the face photograph derived face vector code to the face derived face vector code , the graphic extracted face vector code, or both to develop a second similarity value; comparing the second similarity value to the first threshold value or a second threshold value, and based on the comparing, generating a second validation indicator 13. (currently amended) The system of claim 9 further comprising transmitting the face derived face vector code , the graphic extracted face vector code, or both to a trusted entity and the trusted entity comparing the face derived face vector code, the graphic extracted face vector code, or both to trusted face vector feature codes stored or generated at the trusted entity. 14.18 (currently amended) A method for verifying the validity of an identification document and identity of a person identified by the identification document comprising: capturing one or more images of the graphic on the identification document; processing one or more of the one or more images of the graphic to extract a graphic code , the graphic code comprising data derived from an image of the person’s face , but which cannot be reverse processed to identify the person from which it was derived; transmitting the graphic code to a trusted entity19; at the trusted entity, processing the graphic code or other data sent to the trusted entity to search for a matching trusted face feature code, the trusted face feature code comprising data derived from a person’s face, but which cannot be reverse processed to generate an image or likeness of a face from which it was derived20; {comparing the graphic code to the trusted face feature code to develop a first21 similarity value}22; {{capturing one or more images of a face of the person presenting}} the identification document, the person being physically present in front of the camera; {{processing one or more of the one or more images of the face of the person presenting}} the identification document to calculate a face derived face vector code, the face derived face vector code cannot be reverse processed to 23 identify the person from which it was derived; comparing the graphic code to the face derived face vector code to develop a second similarity value ; and providing the first similarity value and the second similarity value to a requesting entity, the requesting entity comprising an entity that is requesting the verification of the validity of the identification document and identity of the person identified by the identification document24. 14.25 (currently amended) A method for verifying the validity of an identification document and identity of a person identified by the identification document comprising: {capturing one or more images of the graphic on the identification document; processing one or more of the one or more images of the graphic to extract a graphic code, the graphic code comprising data derived from an image of the person’s face , but which can not be reverse processed} to identify the person from which it was derived; transmitting the graphic code to a trusted entity26; [at the trusted entity, processing the graphic code or other data sent to the trusted entity to search for a matching trusted face feature code, the trusted face feature code comprising data derived from a person’s face, but which can]27 not be reverse processed to generate an image likeness of a face from which it was derived ; comparing the graphic code to the trusted face feature code to develop a first similarity value; {{capturing one or more images of a face of the person}} presenting the identification document, the person being physically present in front of the camera; {{processing one or more of the one or more images of the face of the person}}28 presenting the identification document to calculate a face derived face vector code, the face derived face vector code cannot be reverse processed to identify the person from which it was derived; comparing the graphic code to the face derived face vector code to develop a second similarity value; and [providing the first similarity value and the second similarity value to a requesting entity, the requesting entity comprising an entity that is requesting the verification of the validity of the identification document and identity of the person identified by the identification document]29. 15. (original) The method of claim 14, wherein the identification document is a driver’s license, passport, or an identification card. 16.30 (original) The method of claim 14 wherein the trusted entity is the entity that generated the identification document. 16.31 (original) The method of claim 14 wherein the trusted entity is the entity that generated the identification document. 17. (currently amended) The method of claim 14, wherein the identification document includes a photograph of a face, and the method further comprises: capturing one or more images of the photograph of the face on the identification document with a digital camera; processing the one or more images of the photograph to generate an identification document photograph code , {{{the identification document photograph code is not capable of being reverse processed to generate the face in the photograph;}}}32 comparing the identification document photograph code to the trusted face feature code to develop a third second similarity value; transmitting the third second similarity value to the requesting entity. 18.33 (original) The method of claim 14 wherein the graphic code includes information from text contained on the identification document or from an identity record stored on an identity issuer’s database. 1. A method of verifiably encoding data representing two or more people as a machine readable graphic on an item, the method comprising: capturing one or more first images of a first person’s face with a digital camera; capturing one or more second images of a second person’s face; processing the one or more first images of the first person’s face to generate first face-derived feature vector data, the first face - derived feature vector data representing the first person’s face , wherein the first face-derived feature vector data is not capable of being processed to generate an image of the first person’s face ; processing the one or more second images of the second person’s face to generate second face-derived feature vector data, the second face-derived feature vector data representing the second person’s face, {{{{{{{{wherein the second face-derived feature vector data is not capable of being processed to generate an image of the second person’s face}}}}}}}}34; capturing one or more third images of the machine readable graphic on the item; processing the one or more third images of the machine readable graphic to extract first graphic - derived face feature vector data and second graphic-derived feature vector data, wherein the first graphic - derived face feature vector data and the second graphic-derived feature vector data cannot be reverse processed to generate an image of the first person’s face or the second person’s face; comparing the first face - derived feature vector data to the first graphic - derived feature vector data and calculating a first similarity value; comparing the second face-derived feature vector data to the second graphic-derived feature vector data and calculating a second similarity value or modifying the first similarity value; and comparing the first similarity value to a first threshold value, and based on the comparing , generating a first validation indicator that represents a likelihood that the machine readable graphic , and the item having the machine readable graphic thereon , is associated with the first person; and {{{if the second similarity value was generated, comparing the second similarity value to a second threshold value, and based on the comparing, generating a second validation indicator that represents the likelihood that the machine readable graphic, and the item having the machine readable graphic thereon, is associated with the second person}}}. 2. The method of claim 1, wherein the item is one of the following: driver’s license, identification card, passport, diploma, education transcript, credit card, debit card, airline ticket, shipping label, event ticket, voting ballot, or title of ownership. 3. The method of claim 1, wherein the first face-derived feature vector data and the second face-derived feature vector data comprise a string of alpha and numeric values that are encoded and stored in the graphic. 4. The method of claim 1 wherein the item includes a picture of the first person ‘s face, the second person’s face, or both. 5. The method of claim 4 wherein the method further comprises: capturing, with the digital camera, one or more images of a photograph of at least one of the first person’s face and second person’s face that are on the item; processing the one or more images of the photograph to generate photograph - derived face feature vector data ; comparing the photograph - derived face feature vector data to at least one of the first face - derived feature vector data, the second face-derived feature vector data, or the graphic - derived feature vector data, to develop a n additional similarity value; and comparing the additional similarity value to the first threshold value or the second threshold value, and based on the comparing, generating a n additional validation indicator. 6. The method of claim 1, wherein the at least one of the first graphic-derived feature vector data and the second graphic-derived feature vector data is created by a trusted entity from a trusted face photo of the first person and the second person. 7. The method of claim 1, wherein the first similarity value must be greater than or equal to the first threshold value for the machine readable graphic to be associated with the first person , and the second similarity value, if generated, must be greater than or equal to the second threshold value for the machine readable graphic to be associated with the second person. 8. The method of claim 1, further comprising transmitting the first face - derived feature vector data, the second face- derived feature vector data, and the graphic derived feature vector data to a trusted entity and the trusted entity comparing the first face - derived feature vector data, the second face-derived feature vector data and the graphic derived feature vector data, to trusted face feature vector stored at the trusted entity. 9. A system to verify a graphic located on a document is associated with a first person and a second person , the system comprising: a camera configured to capture at least a first facial image of the first person, at least a second facial image of the second person, and an image of the graphic located on the document; a processor configured to execute machine-readable code stored in a non-transitory state in a memory; the memory storing the machine executable code in the non-transitory state, the machine-readable code configured to: process the first facial image of the first person to generate a first face - derived code, {the first face - derived code representing the first person's face}, but is not capable of being processed to generate an image of the first person; process the second facial image of the second person to generate a second face-derived code, {the second face-derived code representing the second person's face}, but is not capable of being processed to generate a face image of the second person; process the image of the graphic to generate a graphic extracted code, the graphic extracted code representing the first person's face and the second person's face , but is not capable of being processed to generate an image of the first person or the second person; and compare the at least a portion of the first face - derived code and at least a portion of the second face -derived code to at least a portion of the graphic extracted code to develop a similarity value. 1. A method of verifiably encoding data representing two or more people as a machine readable graphic on an item, the method comprising: capturing one or more first images of a first person's face with a digital camera; capturing one or more second images of a second person 's face; processing the one or more first image s of the first person's face to generate first face - derived feature vector data, {{ the first face - derived feature vector data representing the first person's face}}, wherein the first face-derived feature vector data is not capable of being processed to generate an image of the first person 's face; processing the one or more second images of the second person's face to generate second face-derived feature vector data, {{the second face-derived feature vector data representing the second person's face}}, wherein the second face-derived feature vector data is not capable of being processed to generate an image of the second person's face; {capturing one or more third images of the machine readable graphic on the item}; processing the one or more third images of the machine readable graphic to {{{extract first graphic - derived face feature vector data and second graphic-derived feature vector data}}} , wherein the first graphic - derived face feature vector data and the second graphic-derived feature vector data can not be reverse processed to generate an image of the first person 's face or the second person's face; comparing the first face - derived feature vector data to the first graphic - derived feature vector data and calculating a first similarity value ; comparing the second face-derived feature vector data to the second graphic-derived feature vector data and calculating a second similarity value or modifying the first similarity value; and comparing the first similarity value to a first threshold value, and based on the comparing , generating a first validation indicator that represents a likelihood that the machine readable graphic , and the item having the machine readable graphic thereon , is associated with the first person ; and if the second similarity value was generated, comparing the second similarity value to a second threshold value, and based on the comparing, generating a second validation indicator that represents the likelihood that the machine readable graphic, and the item having the machine readable graphic thereon, is associated with the second person. 2. The method of claim 1, wherein the item is one of the following: driver’s license, identification card, passport, diploma, education transcript, credit card, debit card, airline ticket, shipping label, event ticket, voting ballot , or title of ownership. 3. The method of claim 1, wherein the first face - derived feature vector data and the second face -derived feature vector data comprise a string of alpha and numeric values that are encoded and stored in the graphic. 5. The method of claim 4 wherein the method further comprises: capturing, with the digital camera, one or more images of a photograph of at least one of the first person ’s face and second person’s face that are on the item; processing the one or more images of the photograph to generate photograph - derived face feature vector data; comparing the photograph - derived face feature vector data to at least one of the first face - derived feature vector data, the second face-derived feature vector data , or the graphic - derived feature vector data, to develop a n additional similarity value; and comparing the additional similarity value to the first threshold value or the second threshold value, and based on the comparing, generating a n additional validation indicator. 8. The method of claim 1, further comprising transmitting the first face - derived feature vector data , the second face- derived feature vector data, and the graphic derived feature vector data to a trusted entity and the trusted entity comparing the first face - derived feature vector data, the second face-derived feature vector data and the graphic derived feature vector data, to trusted face feature vector stored at the trusted entity. 14. A method for verifying an association of a document with two or more people identified in the identification document comprising: capturing one or more images of a graphic on the document; processing at least one of the one or more images of the graphic to extract a code embedded in the graphic , the graphic derived data comprising data created from a first image of at least a first person's face and a second image of a second person's face, wherein {{{{{the graphic derived data can not be processed to}}}}} generate an image of the first person or the second person; {{capturing one or more images of a person presenting}} themselves as the first person; {{processing the one or more images of the person presenting}} themselves as the first person to create a first facial image data; capturing one or more images of a person presenting themselves as the second person; processing the one or more images of the person presenting themselves as the second person to create a second facial image data; {comparing the first facial image data to at least a portion of the graphic derived data; comparing the second facial image data to at least a portion of the graphic derived data; responsive to the comparing, generating a similarity value} that represents a likelihood that the person presenting themselves as the first person is the first person and that the person presenting themselves as the second person is the second person ; processing the graphic derived data to extract document data, the document data representing one or more items if information located on the document. 1. A method of verifiably encoding data representing two or more people as a machine readable graphic on an item, the method comprising: {{capturing one or more first image s of a first person's face}} with a digital camera; {{capturing one or more second images of a second person's face}}; {{processing the one or more first images of the first person's face to generate first face-derived feature vector data, the first face-derived feature vector data}} representing the first person's face, {{{wherein the first face-derived feature vector data is not capable of being processed to generate an image of the first person 's face}}}; processing the one or more second images of the second person's face to generate second face -derived feature vector data , the second face- derived feature vector data representing the second person's face, wherein the second face-derived feature vector data is not capable of being processed to generate an image of the second person's face35; {capturing one or more third images of the machine readable graphic on the item; processing the one or more third images of the machine readable graphic to extract first graphic- derived face feature vector data and second graphic-derived feature vector data, wherein the first graphic -derived face feature vector data and the second graphic-derived feature vector data cannot be reverse processed} to generate an image of the first person's face or the second person's face ; comparing the first face -derived feature vector data to the first graphic-derived feature vector data and calculating a first similarity value; comparing the second face-derived feature vector data to the second graphic - derived feature vector data and calculating a second similarity value or modifying the first similarity value; and {{comparing the first similarity value to a first threshold value, and based on the comparing, generating a first validation indicator that represents a likelihood that the machine readable graphic , and the item having the machine readable graphic thereon, is associated with the first person}}; and if the second similarity value was generated, comparing the second similarity value to a second threshold value, and based on the comparing, generating a second validation indicator that represents the likelihood that the machine readable graphic, and the item having the machine readable graphic thereon, is associated with the second person. 15. The method of claim 14 further comprising: extracting an encoded digital signature from the graphic derived data; processing a portion of the graphic derived data to generate a calculated digital signature; comparing the encoded digital signature to the calculated digital signature; responsive to the encoded digital signature not matching the calculated digital signature, terminating the method of claim 14. 16. The method of claim 14 wherein the document is a driver's license, passport, property title, financial document, contract, transcript, an identification card , or the graphic is located on an electronic display. 6. The method of claim 1, wherein the at least one of the first graphic-derived feature vector data and the second graphic-derived feature vector data is created by a trusted entity from a trusted face photo of the first person and the second person. 13. The system of claim 9 further comprising transmitting the first face-derived code, the second face-derived code, and the graphic extracted code to a trusted entity and the trusted entity comparing the first face-derived code, the second face-derived code, and the graphic extracted code to trusted codes stored or generated at the trusted entity. 17. The method of claim 14 wherein the graphic is created by and printed on the document by an issuing authority. 18. The method of claim 14 wherein the document includes a photograph of the first person's face, the second person's face, or both, and the method further comprises: capturing one or more images of the photograph of the first person's face , the second person's face, or both from the identification document using a digital camera; processing the one or more images of the photograph of the first person's face, the second person's face, or both from the identification document to generate an identification document photograph code ; comparing the identification document photograph code to at least a portion of the graphic derived data to develop a second similarity value; and transmitting the second similarity value to a requesting entity. 19. The method of claim 14 wherein the code includes information from text contained on the document that is captured as part of an optical character recognition process. 20. The method of claim 14 further comprising {{{{{{providing the similarity value to a requesting entity, the requesting entity comprising an entity that is requesting the verification of the association of the document with the two or more people identified in the document}}}}}}. 17. The method of claim 14 wherein the graphic is created by and printed on the document by an issuing authority. Table 1 The table (Table 1) above shows that independent claims 1, 9 of this Application is not identical to the claims of US 2021/0011986 A1. However, the claims are not patentably distinct. The US 2021/0011986 A1 is narrower than independent claims 1, 9 since it includes several additional limitations not found in claim 1, 9 of the instant Application. PNG media_image3.png 2066 1764 media_image3.png Greyscale PNG media_image4.png 1659 1689 media_image4.png Greyscale PNG media_image5.png 1716 1710 media_image5.png Greyscale Re claims 1 and 9, US 2026/0024378 A1 does not teach the difference of claims 1,9 (claim 1 representative) of : wherein the person is live and physically present in front of the camera. Tussy teaches the difference of claims 1,9 (claim 1 representative) of: wherein the person is live and physically present in front of the camera (as mapped in the 35 USC 103 rejection of claim 1, below: Claim(s) 1,2,3,4,5,6,7,8 and 9,10,11,12,13 and 14,15,16,17,18 is/are rejected under 35 U.S.C. 103 as being unpatentable over GRIESER et al. (EP 3 889 922 A1) with SEARCH machine translation plus SEARCH machine translation II in view of YOSHIDA (WO 2019/132047 A1) with SEARCH machine translation and Tussy (US 2021/0011986 A1).). Thus it would have been obvious to combine the claims of US 2026/0024378 A1 with Tussy’s (US 2021/0011986 A1) teachings of a camera for similar reasons using similar steps as in the 35 USC 103 rejection of claims 1,2,3,4,5,6,7,8 and 9,10,11,12,13 and 14,15,16,17,18. Claim 14 is rejected like claims 1 and 9: Re claim 14, US 2026/0024378 A1 does not teach the difference of claim 14 of: --comparing the graphic code to the trusted face feature code to develop a first similarity value; capturing one or more images of a face of the person presenting the identification document, the person being physically present in front of the camera;… providing the first similarity value and the second similarity value to a requesting entity, the requesting entity comprising an entity that is requesting the verification of the validity of the identification document and identity of the person identified by the identification document.--: PNG media_image6.png 1986 1694 media_image6.png Greyscale US 2021/0011986 A1 teach the difference of claim 14 of: --comparing the graphic code to the trusted face feature code (or likewise “various methods of comparison36”, [0265] last S: such as “comparing the unique ID code to a database of ID codes” [0044]) to develop a first similarity value (or likewise “so that similarities and differences may be determined”, [0265] last S, via: [0044] Also disclosed herein is a system for remote identity verification comprising a computing device comprising a processor configured to execute machine executable code, a screen configured to provide an interface to the user, a camera configured to capture images, and one or more memories configured to store machine executable code which, when executed by the processor, cause the computing device to perform the following steps. These steps include recording at least one captured image of the user taken with the camera of the computing device and receive a unique ID code from the user. Then, processing at least the at least one captured image to create a captured image facemap and encrypt the captured image facemap and the unique ID code to create first encrypted user data. Then, transmitting the first encrypted user data to a liveness verification server. At the liveness verification server there is a processor and memory storing machine executable code configured to, when executed by the processor, cause the liveness verification server to perform the following steps. Receive and decrypt the first encrypted user data and to obtain the captured image facemap. Then process the captured image facemap to verify liveness of the user and, responsive to a determination that the captured image facemap was captured from a live person, encrypt the captured image facemap and the unique ID code to create second encrypted user data. Then, transmitting the second encrypted user data to a trusted image server. The trusted image server comprises a server having a processor and memory storing machine executable code configured to, when executed by the processor, cause the trusted image server to receive and decrypt the second encrypted user data to obtain the captured image facemap and the unique ID code. Then, comparing the unique ID code to a database of ID codes to locate a matching ID code. Responsive to a match between the unique ID code and an ID code in the database of ID codes, retrieving a trusted image that is associated with the unique ID code and generate a trusted image facemap based on the trusted image. Then comparing the captured image facemap to the trusted image facemap and, responsive to a match between the captured image facemap to the trusted image facemap, sending a message to the computing device, a third party server, or both of the match. Responsive to a match not occurring between the captured image facemap and the trusted image facemap, sending a message to the computing device, a third-party server, or both of the failure to match. [0265] For facial recognition systems with a server component, the same facial recognition algorithm can be loaded onto the server as is running in an application on the smart device. This allows only the template to be transferred to the device instead of the biometric reading itself (e.g., the facial images, fingerprints scans, etc.). For example, in step 1705, the biometric information may be the biometric template instead of an image from the root identity profile. The algorithms located on different devices/servers must be configured so that the templates they create are homogenous and can be compared. That is, if the algorithms output data in different formats, the resulting biometric templates/data format is incompatible, and no matching can occur because the similar facial features would not be represented by similar biometric template data patterns. The term template is defined herein as biometric data points represented by a string of numbers or other data formed in a consistently formatted pattern so that similarities and differences may be determined via various methods of comparison.); capturing one or more images of a face of the person presenting the identification document (or likewise “providing documents” [0272]), the person being physically present in front of the camera (fig. 1:108: this front of camera limitation is mapped in the double patenting rejection of claims 1 and 9 via: [0272] To verify biometric data, an individual typically is required to enter a bank branch, a government office such as a DMV or police station, or other “trusted” location to have his/her biometric data collected. For example, a bank may require a photograph, a fingerprint, or a voice recording to open certain types of accounts. The obtained biometric data is then linked to the person and the account. This in-person collection of biometric data has typically been required because there was no other way to trust that an individual was indeed who they claimed to be. Through the in-person collection, the identification is verified by, for example, the person providing documents with their name and photograph issued by a governing body.);… providing the {{{first}}} similarity37 value {{{and38 the second similarity value}}} to a requesting entity, the requesting entity comprising an entity that is requesting the verification of the validity of the identification document {{{and identity}}} of the person identified by the identification document (or likewise/”arranged39 or combined…as” “an…entity requesting…the person is who they assert to be…is verified…to the authentication device which may be any of the servers or devices shown in FIG. 16”, reproduced below, via: “[0259] The smart device 1612 may be referred to as the authentication device because it is the device that is used for authentication. The user of the smart device 1612 then articulates the camera 1614 so that the user's face can be captured by the device's camera 1614, in step 1707. As described above, one or more images may be captured. The images may be captured with the camera at different distances from the user or the user at different distances from the camera. The biometric data (profile or template) downloaded from the server 1630 to the authentication device can now be compared in step 1709. In one embodiment the trusted template or the trusted image may be downloaded to the smart device (authentication device). For example, each trusted image is converted into a biometric template by a facial recognition algorithm for comparison. Upon comparison, if the templates are similar enough based on the thresholds set by, for example, an application publisher or entity requesting authentication, the smart device captured image (device identity) and the previously captured image (root identity) can be considered a match in step 1711. Thus, the person is who they assert to be, and identity is verified. Access may then be granted, or the business transaction completed, travel allowed, or any other activity authorized, or the signup/enrollment process may then be completed based on the matching images or templated in step 1713. If there is no match in step 1711, the access is denied in step 1715.)” “[0260] As describe above, the trusted biometric information (profile or template) is sent from a remote server to the authenticating device. In other embodiments other data exchange schemes are possible. In one embodiment, the trusted biometric information stored on a root identity server 1630 and the authentication biometric information (captured during an authentication session) is uploaded to the root identify server 1630. The root identify server 1630 is equipped with a memory (storing software-machine readable code) and a processor configured to execute authentication algorithms. The authentication algorithms may be for identity verification, liveness, or both. The results of the authentication request are the return to the authentication device which may be any of the servers or devices shown in FIG. 16.”--. PNG media_image7.png 647 997 media_image7.png Greyscale 2152.02(b) Described in a Printed Publication [R-11.2013] [Editor Note: This MPEP section is only applicable to applications subject to examination under the first inventor to file (FITF) provisions of the AIA as set forth in 35 U.S.C. 100 (note). See MPEP § 2159 et seq. to determine whether an application is subject to examination under the FITF provisions, and MPEP § 2131-MPEP § 2138 for examination of applications subject to pre-AIA 35 U.S.C. 102.] If a claimed invention is described in a patent, published patent application, or printed publication, such a document may be available as prior art under AIA 35 U.S.C. 102(a)(1). Both pre-AIA 35 U.S.C. 102(a) and (b) and AIA 35 U.S.C. 102(a)(1) use the term "described" with respect to an invention in a prior art printed publication. Likewise, AIA 35 U.S.C. 102(a)(2) uses that term with respect to U.S. patents, U.S. patent application publications, and WIPO published applications. Thus, the Office does not view the AIA as changing the extent to which a claimed invention must be described for a prior art document to anticipate the claimed invention under 35 U.S.C. 102. While the conditions for patentability of AIA 35 U.S.C. 112(a) require a written description of the claimed invention that would have enabled a person skilled in the art to make as well as use the invention, the prior art provisions of AIA 35 U.S.C. 102(a)(1) and (a)(2) require only that the claimed invention is "described" in a prior art document (patent, published patent application, or printed publication). The two basic requirements that must be met by a prior art document in order to describe a claimed invention such that it is anticipated under AIA 35 U.S.C. 102 are the same as those under pre-AIA 35 U.S.C. 102. First, "each and every element of the claimed invention" must be disclosed either explicitly or inherently, and the elements must be "arranged or combined [via combining paragraphs [0259][0260] forming an orderly/tidy/harmonious sentence] in the same way as in the claim [claim 14]." See In re Gleave, 560 F.3d 1331, 1334, 90 USPQ2d 1235, 1237-38 (Fed. Cir. 2009), citing Eli Lilly & Co. v. Zenith Goldline Pharms., Inc., 471 F.3d 1369, 1375, 81 USPQ2d 1324,1328 (Fed. Cir. 2006); Net MoneyIN, Inc. v. VeriSign, Inc., 545 F.3d 1359, 1370, 88 USPQ2d 1751, 1759 (Fed. Cir. 2008); In re Bond, 910 F.2d 831, 832-33, 15 USPQ2d 1566, 1567 (Fed. Cir. 1990). Second, a person of ordinary skill in the art must have been enabled to make the invention without undue experimentation. See Gleave, 560 F.3d at 1334, 90 USPQ2d at 1238 (citing Impax Labs., Inc. v. Aventis Pharms. Inc., 545 F.3d 1312, 1314, 88 USPQ2d 1381, 1383 (Fed. Cir. 2008), and In re LeGrice, 301 F.2d 929, 940-44, 133 USPQ 365, 372 (CCPA 1962)). Thus, in order for a prior art document to describe a claimed invention such that it is anticipated under AIA 35 U.S.C. 102(a)(1) or (a)(2), it must disclose all elements of the claimed invention arranged [via combining paragraphs [0259][0260] forming an orderly/tidy/harmonious sentence] as they are in the claim [claim 14], and also provide sufficient guidance to enable a person skilled in the art to make the claimed invention. There is, however, no requirement that a prior art document meet the "how to use" requirement of 35 U.S.C. 112(a) in order to qualify as prior art. See Gleave, 560 F.3d at 1334, 90 USPQ2d at 1237-38; see also In re Schoenwald, 964 F.2d 1122, 1124, 22 USPQ2d 1671, 1673 (Fed. Cir. 1992) (holding that a claimed compound was anticipated even though the prior art reference did not disclose a use for the compound); Schering Corp. v. Geneva Pharms., Inc., 339 F.3d 1373, 1380-81, 67 USPQ2d 1664, 1670 (Fed. Cir. 2003) (pointing out that actually reducing the invention to practice is not necessary in order for a prior art reference to anticipate); Impax Labs, 468 F.3d at 1382 (stating that "proof of efficacy is not required for a prior art reference to be enabling for purposes of anticipation"). Furthermore, compliance with the "how to make" requirement is judged from the viewpoint of a person of ordinary skill in the art, and thus does not require that the prior art document explicitly disclose information within the knowledge of such a person. See In re Donohue, 766 F.2d 531, 533, 226 USPQ 619, 621 (Fed. Cir. 1985). wherein “arranged” is defined: (tr) to put into a proper, systematic, or decorative order, wherein systematic is defined: characterized by the use of order and planning; methodical, wherein methodical is defined: characterized by method or orderliness; systematic, wherein orderly(-ness) is defined: 1 in order, properly arranged, or tidy 3 harmonious or peaceful (Dictionary.com) Thus it would have been obvious to combine the claims of US 2026/0024378 A1 with Tussy’s (US 2021/0011986 A1) teachings of a camera for similar reasons using similar steps as in the 35 USC 103 rejection of claims 1,2,3,4,5,6,7,8 and 9,10,11,12,13 and 14,15,16,17,18. Response to Arguments Applicant's arguments filed 8/6/2026 have been fully considered but they are not persuasive: Double Patenting After further reconsideration, claims 1-8 and 9-13 and 14-18 are rejected via double patenting: Claims 1-8 and 9-13 and 14-18 provisionally rejected on the ground of nonstatutory double patenting as being unpatentable over claim 1-20 of copending Application No. US 2026/0024378 A1 in view of Tussy (US 2021/0011986 A1). Section 103 Rejection Applicants state in page 9: “This amendment differentiates the claimed subject matter from the Grieser reference. The cited prior art is not directed to validating a person's identity. Grieser is directed to document validation.” In response the preamble’s “of40 validating a person’s identity” does not serve “to limit the claim” since the preamble is not “reciting the purpose or intended use” via MPEP 2111.02 Effect of Preamble [R-07.2022] II. PREAMBLE STATEMENTS RECITING PURPOSE OR INTENDED USE, 2nd para: During examination, statements (“of validating a person’s identity”) in the preamble reciting the purpose or intended use (there is no purpose or intended use in the preamble of claim 1) of the claimed invention must be evaluated to determine whether or not the recited purpose or intended use results in a structural difference (or, in the case of process claims, manipulative difference) between the claimed invention and the prior art. If so, the recitation serves to limit the claim. See, e.g., In re Otto, 312 F.2d 937, 938, 136 USPQ 458, 459 (CCPA 1963) (The claims were directed to a core member for hair curlers and a process of making a core member for hair curlers. The court held that the intended use of hair curling was of no significance to the structure and process of making.); In re Sinex, 309 F.2d 488, 492, 135 USPQ 302, 305 (CCPA 1962) (statement of intended use in an apparatus claim did not distinguish over the prior art apparatus). To satisfy an intended use limitation which is limiting, a prior art structure which is capable of performing the intended use as recited in the preamble meets the claim. See, e.g., In re Schreiber, 128 F.3d 1473, 1477, 44 USPQ2d 1429, 1431 (Fed. Cir. 1997) (anticipation rejection affirmed based on Board’s factual finding that the reference dispenser (a spout disclosed as useful for purposes such as dispensing oil from an oil can) would be capable of dispensing popcorn in the manner set forth in appellant’s claim 1 (a dispensing top for dispensing popcorn in a specified manner)) and cases cited therein. See also MPEP § 2112 - MPEP § 2112.02. Applicant’s arguments, see remarks, page 9, last paragraph, filed 8/6/2026, with respect to the rejection(s) of claim(s) 1 under 35 USC 103 have been fully considered and are persuasive. Therefore, the rejection has been withdrawn. However, upon further consideration, a new ground(s) of rejection is made in view of 35 USC 103: . Claim(s) 1,2,3,4,5,6,7,8 and 9,10,11,12,13 and 14,15,16,17,18 is/are rejected under 35 U.S.C. 103 as being unpatentable over GRIESER et al. (EP 3 889 922 A1) with SEARCH machine translation plus SEARCH machine translation II in view of YOSHIDA (WO 2019/132047 A1) with SEARCH machine translation and Tussy (US 2021/0011986 A1). Applicant's arguments filed 8/6/2026 have been fully considered but they are not persuasive: Applicants state on page 10, 2nd para: These amendments clarify41 that the vector data42 represents the person's face. This contrasts with the Grieser reference, which requires that the data calculated from a document represents the document and is not face data4344. In addition, the same camera is used to capture the image of the graphic code and the person's face. This is not the case in the Grieser reference. The fundamental operation of the Grieser reference is vastly different than the claimed system. During the actual validation process of the Grieser reference, only document images are captured, and not a live, physically present user. In response, Grieser teaches face data or likewise “facial image ”-“data” via page 13, 3rd txt blk: Corresponding embodiments of the invention can have the advantage that the size of the partial images in relation to the size of the overall facial image already contributes to the fact that the characteristics of the face are not completely lost and thus face-individual or document-individual image reference data are generated, however, no reconstruction of the facial image of the person is possible in sufficient quality to be ablet o identify the person with it. Thus the vector data45 representing the person's face does not contrast with the Grieser reference teaching said “facial image”-“data” with not “sufficient quantity” to recognize a person. In response to applicant's argument that the references fail to show certain features of the invention, it is noted that the features upon which applicant relies (i.e., page 10, 2nd para, 3rd S: “the same camera is used to capture the image of the graphic code and the person's face”) are not recited in the rejected claim(s). Although the claims are interpreted in light of the specification, limitations from the specification are not read into the claims. See In re Van Geuns, 988 F.2d 1181, 26 USPQ2d 1057 (Fed. Cir. 1993). In response to applicant's argument that the references fail to show certain features of the invention, it is noted that the features upon which applicant relies (i.e., page 10, last para, 1st S: “comparison…between46 face data”) are not recited in the rejected claim(s). Although the claims are interpreted in light of the specification, limitations from the specification are not read into the claims. See In re Van Geuns, 988 F.2d 1181, 26 USPQ2d 1057 (Fed. Cir. 1993). In contrast, claim 1 says: “comparing the face derived face feature vector data to47484950 the graphic derived face feature vector data to develop a similarity value;” Applicant’s arguments, see remarks, pages 10,11: This claim amendment makes clear that the comparison required by claim 1 is between face data, namely, the face data extracted from the graphic code and the face data from the image of the person's face captured during the validation. This does not occur in the Grieser reference. The Grieser reference never captures a facial image of a live person. Similarly, the Grieser reference does not compare face image data captured from a live person physically in front of the camera because this type of data is never captured in the Grieser reference. , filed 8/6/2026, with respect to the rejection(s) of claim(s) 1 under 35 USC 103 have been fully considered and are persuasive. Therefore, the rejection has been withdrawn. However, upon further consideration, a new ground(s) of rejection is made in view of said: . Claim(s) 1,2,3,4,5,6,7,8 and 9,10,11,12,13 and 14,15,16,17,18 is/are rejected under 35 U.S.C. 103 as being unpatentable over GRIESER et al. (EP 3 889 922 A1) with SEARCH machine translation plus SEARCH machine translation II in view of YOSHIDA (WO 2019/132047 A1) with SEARCH machine translation and Tussy (US 2021/0011986 A1), wherein Tussy teaches capturing a facial image of a live person: PNG media_image8.png 1086 947 media_image8.png Greyscale Applicant's arguments filed 8/6/2026 have been fully considered but they are not persuasive: Applicants state on page 11, 2nd paragraph: There are additional distinguishing features when comparing the method of claim 1 and the combination of the Grieser reference and the Yoshida reference. One such feature is that during the validation process for a document in the Grieser reference, only an image of the document is captured. Applicants are suggesting that a face is captured and a printed graphic51 is captured and that both the face and printed graphic are different. Claim 1 does not make apparent that a face (fig. 26: phone image below) is captured and a printed graphic (fig. 26: 2400) is captured and that both the face and the printed graphic are different: PNG media_image9.png 573 699 media_image9.png Greyscale Additional Differentiating Features in Claims Applicants are suggesting the field of neural networks. The examiner suggests using clear terms of art of neural networks such as “feature vector”. The remarks (filed 6/6/2026) at pages 11,1252 are not consistent with which Markush alternative applicants are applying: The full-list of Markush alternatives is “a face derived feature vector data” (claim 1, lines 5,6): one of the following Markush alternatives of the full-list Markush alternatives (“face derived face feature vector data”) is inconsistently mentioned/used in applicant’s remarks in pages 11,12: “face vector53 data” “face feature vector54 data” “face vector55”. Thus, the examiner suggests using/claiming clear terms of art of neural networks such as “feature56 vector”57 as indicated in applicant’s disclosure: [0488]If the image meets the minimum requirements for subsequent processing, then the operation advances to step 4736. At step 4736 the affined and cropped image data is provided as an input into a DNN (deep neural network) model. The DNN processes the image data using the weighting factors and node algorithms, with optional feedback or recursive processing such as during training. Different algorithms and models may be used to arrive at a unique code, such as for example, a facevector. DNN processing is described herein and is known by those of skill in the art. The output of the DNN model is an n-dimensional feature vector (which may be referred to as a facevector or the outputs of the DNN model may assembled into the n-dimensional feature vector (facevector) at a step 4740. Facevectors are described above. The value of N may be any whole number. The value of N may be defined as the number of characteristics, features or attributes which are analyzed in the image data by the DNN to generate the facevectors. Claim Rejections - 35 USC § 103 The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action: A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made. The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows: 1. Determining the scope and contents of the prior art. 2. Ascertaining the differences between the prior art and the claims at issue. 3. Resolving the level of ordinary skill in the pertinent art. 4. Considering objective evidence present in the application indicating obviousness or nonobviousness. Claim(s) 1,2,3,4,5,6,7,8 and 9,10,11,12,13 and 14,15,16,17,18 is/are rejected under 35 U.S.C. 103 as being unpatentable over GRIESER et al. (EP 3 889 922 A1) with SEARCH machine translation plus SEARCH machine translation II in view of YOSHIDA (WO 2019/132047 A1) with SEARCH machine translation and Tussy (US 2021/0011986 A1). Re 1. (currently amended), GRIESER teaches A method of validating a person’s identity 58 capturing one or more images of the person’s face with a digital camera (fig. 8:802: “Kamera”) , wherein the person59 is live and physically present in front of the camera; processing the one or more images of the person’s face to generate60 a face (“(face) image data”, pg. 26, 6th txt blk) derived61 (A) {{{feature (or “personal”--i.e. face-- “derived” “specific62 information”, pg. 6, 3rd txt blk)63 (&)64 (B) vector}}} data (mapped to both alternatives (A) & (B): or a “test image”: fig. 4A:404:face- “reference data”- “vector”-“recorded”-“characters and logos”: 6th txt blk: fig. 7), the face derived (A) {{{face feature}}} (B) {{{vector}}} data (or likewise said personal-derived-specific-information) representing the person’s face but not capable of being reverse processed (via “ an irreversible, information-loss-prone arithmetic function”, pg. 2, last txt blk) to generate the image of the person’s face from which it was derived; capturing (fig. 8:802: “Kamera”) one or more images of the (code) graphic65 (or likewise “a graphic representation”, machine translation II, pg. 30, penult txt blk, as shown in fig. 3A as a histogram) on6667 the item with the camera PNG media_image10.png 739 1026 media_image10.png Greyscale ); processing one or more of the images of the68 (code) graphic69 (“machine-readable70 zone”, pg. 8, 1st txt blk) code (fig. 7: “MRZ”) to (electromagnetically) extract (via “generated”, pg. 26, 6th txt blk) graphic (or “graphic elements” “position data”, pg. 8, 3rd S)71 derived {{{face}}} (C) {{{feature}}} (“derived” “reference72 data 714,718”, pg. 25, 8th txt blk) (&) (D) {{{vector}}} (“test”-“time”, pg. 26, 6th txt blk)73 data (or likewise extracting frequencies from the histogram graphic via “detected74 frequency”-“frequency distribution”, machine translation II, pg. 13, last txt blk, mapped to both alternatives (C) & (D)) that is stored (via said “recorded”) inside (or likewise inside a histogram classification box via “a corresponding class (bin75)”, machine translation II, pg. 48, 3rd txt blk ) the graphic code such that the graphic derived {{{face feature vector}}} (“test”-“time”) data represents the person’s face but cannot be reverse processed to generate the image of the person’s face from which it was derived; comparing (via “a similarity indicator”, pg. 26, 6th txt blk) the (“issuing”, pg. 26, 6th txt blk) face derived {{{face feature vector}}} data to the graphic (“test”-“time”) derived {{{face feature vector}}}76 data to develop a similarity value; and comparing the similarity value to a first threshold (“1:1 ratio”, pg. 26, 6th txt blk) value, and based on the comparing to7778 the first threshold value, generating a validation (“reference”, pg. 8, 5th txt blk or in general data comparison: pg. 10, 6th txt blk) indicator that represents the (strong) likelihood (via “The exact79 positions and/or sizes of individual further optically detectable features”, pg. 26, 3rd text blk) that the graphic80 (and thus implicitly also the dissimilarity) of two compared entities”, pg. 13, 6th txt blk). GRIESER does not teach the difference of claim 1 of: (the person)8182 is live and physically present in front of (the camera)…83 first (threshold). YOSHIDA faces a similar problem as applicants (“authentication…face…error”, pg. 37, 3rd txt blk) and teaches the difference of claim 1: a) (data that is stored) (“Encrypted information”, pg. 35, last txt blk) inside (“the first code”, pg. 90: “40.”) (the graphic code)84…85 b) (“a region having a high density of reference dots using a”) first (“code”-“predetermined threshold from the surrounding dark cells starting from the central coordinate value of the dark cell obtained by the first code”, pg. 51, 4th txt blk) (threshold). Since GRIESER teaches security and faces a problem (“no…security… guarantee”, pg. 2, 3rd txt blk) as applicant’s, one of skill in the art of security can make GRIESER’s be as YOSHIDA’s seeing in the change “security can be enhanced by displaying only a part of the photo, date of birth, address and the like included in the read data, and hiding the other information”, YOSHIDA, pg. 39, 5th txt blk: PNG media_image11.png 716 1130 media_image11.png Greyscale The combination of GRIESER-YOSHIDA does not teach the remaining difference of claim 1: (the person)8687 is live and physically present in front of (the camera)…88 PNG media_image8.png 1086 947 media_image8.png Greyscale Tussy teaches difference of claim 1: (the person)8990 is live and physically present in front of (the camera)…91 (or likewise “a live human user, present in person in front of the camera”: [0325] At a step 2228, the first remote server receives and decrypts the received encrypted 3D facescan, and identification number. In other embodiments, images may be sent instead of a facescan or other biometric information may be sent to perform the liveness check. Next, at a step 2232 the first remote server (server A) performs liveness checks or liveness verification to determine whether the 3D facescan (which represents an image of the user) represents a live user and was captured directly from a live, physical user, and thus not a photo, video, mask, image, spoof artifact, or some other representation made to look like a live person. At decision step 2236, a determination is made whether the 3D facescan represents a live person and was collected first generation from a live human user, present in person in front of the camera. The 3D facescan may be time-stamped to prevent reuse in the future and is therefore not re-playable. If the 3D facescan is not a representation of a live person, then the operation advances to a step 2240 and the operation ends.). Since GRIESER teaches a problem using passports “is not sufficient” such as being “tampered” or “manipulated” via page 3, last para to page 4, 1st para: However, not all value and security documents also have corresponding data memories and / or microprocessors in order to guarantee the manipulation security of the document and / or its information content by means of algorithmic and /or cryptographic methods. Even if these components are present, their use in the course of an integrity check is often too time-consuming or too complex. Said electronic means for checking the integrity are often inadequate, namely when the integrity of the document is to be based on purely optical features (holograms, facial image of the owner of the document, handwritten signature of the owner, etc.) at least on some occasions. For example, the facial image of a person on the passport or identity card or employee ID is used is printed on this person, regularly of proof to other persons that the owner of the document is the person for whom the ID was issued. In such scenarios, it is not sufficient to just ensure that electronic components or data storage devices of the document are of integrity, i.e. that they have not been tampered with. Rather, it must also and in particular be ensured that the optically detectable, personal data of the document are not manipulated or that a corresponding manipulation can be identified quickly and reliably. and Tussy teaches a similar problem with passports: [0283] Although described in financial terms, it is also contemplated that other actions may be used to build trust that biometric information captured when the action occurs, and the resulting trusted biometric profile developed over time is accurate and trusted. For example, in one embodiment, the authentication system may be used as a time-clock or access control system at a person's place of employment. Every time the user clocks into work or enters the building using the system for access control, their biometric information is captured and used to build trust in their identity. It is assumed that the person attending work is the actual person and not a person attempting to commit fraud or establish a false identity. Likewise, this process could occur at a doctor's office as part of a medical exam, dentist office, for donation of money, when obtaining or renewing a driver license or passport, attending school, or any other activity that would not be performed by a person attempting to commit fraud. GPS data may be combined with this process to verify that a person clocking into work is at the work site. , one of skill in the art could or would have done is consult others for the fix making GREISER’s of combination of GRIESER-YOSHIDA be as Tussy’s seeing in the change goodness (additional motivation) of an “accurate” “biometric” for the “passport”, Tussy [0283]: [0283] Although described in financial terms, it is also contemplated that other actions may be used to build trust that biometric information captured when the action occurs, and the resulting trusted biometric profile developed over time is accurate and trusted. For example, in one embodiment, the authentication system may be used as a time-clock or access control system at a person's place of employment. Every time the user clocks into work or enters the building using the system for access control, their biometric information is captured and used to build trust in their identity. It is assumed that the person attending work is the actual person and not a person attempting to commit fraud or establish a false identity. Likewise, this process could occur at a doctor's office as part of a medical exam, dentist office, for donation of money, when obtaining or renewing a driver license or passport, attending school, or any other activity that would not be performed by a person attempting to commit fraud. GPS data may be combined with this process to verify that a person clocking into work is at the work site. via explicit, creative, routine, inferential Supreme Court steps: A,B,C for achieving said “accurate” “biometric” for the “passport: A) create a Document Capturing Program based on GREISER’s teaching of FIG. 1A via page 36, last para continued on page 37 1st para: A1) at step 106, create code calling a Passport Transaction Program: A1.1) input the “image reference data linked to” to a passport ID of step 106 to the Passport Transaction Program: PNG media_image12.png 710 1064 media_image12.png Greyscale Figure 1A illustrates an exemplary flow diagram of an embodiment of the method according to the invention for enabling an integrity check of a document. The method can be carried out, for example, in the course of producing (issuing), personalizing and / or registering a document. The method can for example be carried out by the components of a system 800 as shown in FIG. In the following, therefore, the method according to Figure 1A in combination with the system according to Figure 8 described. B) install the Document Capturing Program into GRIESER’s fig. 9:920: “Inspection system” in a computer at the Passport Issuing Office: PNG media_image13.png 799 1000 media_image13.png Greyscale C) create the Passport Transaction Program based on Tussy’s fig. 18: C1) creating code inputting said “image reference data linked to” to a passport ID at step 1807:“Request Transaction and Capture Authentication Biometric Data” PNG media_image14.png 1113 937 media_image14.png Greyscale PNG media_image15.png 1894 1063 media_image15.png Greyscale D) install the Passport Transaction Program into GRIESER’s fig. 9:920: “Inspection system” as said computer at the Passport Issuing Office: PNG media_image13.png 799 1000 media_image13.png Greyscale E) At the Passports Office, issue/renew the passport by running the Document Capturing Program calling the Passport Transaction Program: PNG media_image15.png 1894 1063 media_image15.png Greyscale Figure 1A illustrates an exemplary flow diagram of an embodiment of the method according to the invention for enabling an integrity check of a document. The method can be carried out, for example, in the course of producing (issuing), personalizing and / or registering a document. The method can for example be carried out by the components of a system 800 as shown in FIG. In the following, therefore, the method according to Figure 1A in combination with the system according to Figure 8 described. F) see what happened (I foresee goodness (motivation): a trusted and accurate passport addressing GRIESER’s problem of a passport that has been tampered or manipulated: facial image of a person on the passport or identity card or employee ID is used is printed on this person, regularly of proof to other persons that the owner of the document is the person for whom the ID was issued. In such scenarios, it is not sufficient to just ensure that electronic components or data storage devices of the document are of integrity, i.e. that they have not been tampered with. Rather, it must also and in particular be ensured that the optically detectable, personal data of the document are not manipulated or that a corresponding manipulation can be identified quickly and reliably. [0283] Although described in financial terms, it is also contemplated that other actions may be used to build trust that biometric information captured when the action occurs, and the resulting trusted biometric profile developed over time is accurate and trusted. For example, in one embodiment, the authentication system may be used as a time-clock or access control system at a person's place of employment. Every time the user clocks into work or enters the building using the system for access control, their biometric information is captured and used to build trust in their identity. It is assumed that the person attending work is the actual person and not a person attempting to commit fraud or establish a false identity. Likewise, this process could occur at a doctor's office as part of a medical exam, dentist office, for donation of money, when obtaining or renewing a driver license or passport, attending school, or any other activity that would not be performed by a person attempting to commit fraud. GPS data may be combined with this process to verify that a person clocking into work is at the work site.). Re 2. (original) , GRIESER of the combination of GRIESER,YOSHIDA teaches The method of claim 1, wherein the item is one of the following: driver’s license, identification card, passport, diploma, education transcript, credit card, debit card, airline ticket, shipping label, event ticket, voting ballot, or title of ownership (“An identity ocument can be, for example, an identity card, a passport, an employee ID or a personalized document of value (for example credit card)”, pg. 13, 2nd txt blk). Re 3. (currently amended) , GRIESER of the combination of GRIESER,YOSHIDA teaches The method of claim 1 wherein the face derived face feature vector data comprises a string (“or document type-related alphanumeric character strings 710”, pg. 25, 8th txt blk) of alpha and numeric values that is Re 4. (original), GRIESER of the combination of GRIESER,YOSHIDA teaches The method of claim 1 wherein the item includes a picture of the person (“in particular a facial picture of the person”, pg. 4, 6th txt blk) . Re 5. (currently amended), GRIESER of the combination of GRIESER,YOSHIDA teaches The method of claim 4 wherein the method further comprises: capturing, with the camera, one or more photograph images (“of at least a part of a document by an optical sensor”, pg. 2, last text blk) of a photograph of the person’s face that is on the item; processing the one or more photo images to generate a photograph derived face (E) feature (&) (F) vector data (mapped to Markush alternative (E): “them”-“derived”-“reference data”, pg. 22, last txt blk) which represents the person’s face but is not capable of being reverse processed to generate an image of the person shown in the photograph; comparing (via said similarity indicator) the photograph derived face (E) feature (F) vector data to (G) the face derived (A) face feature (B) vector data (via at said test-time), (H) the graphic derived (C) face feature (D) vector data, or (I) both to develop a second similarity value; comparing the second similarity (“recorded size”-“distance”, pg. 26, 5th txt blk) value to (J) the first threshold value or (K) a second threshold value, and based on the comparing, generating a second validation indicator (“each”, pg. 7, 3rd txt blk). Re 6. (currently amended), GRIESER of the combination of GRIESER,YOSHIDA teaches The method of claim 1 wherein the face derived face feature vector data is created (via said generated) by a trusted (via said recognition) entity from a trusted face photo (via “recognizing…facial images”, pg. 22 8th txt blk resulting in recognized identified verified trusted face images) of the person. Re 7. (currently amended), GRIESER of the combination of GRIESER-YOSHIDA -Tussy teaches The method of claim 1 wherein the similarity value must be the same as or greater than (“not manipulated”, pg. 18 6th txt blk) the92 threshold93 value for the person’s identity to be validated (or likewise “ the person94 for whom the document was issued or personalized would like to authenticate himself to an authority or other entity with the aid of this document”, machine translation II, pg. 49, 3rd txt blk) GRIESER of the combination of GRIESER-YOSHIDA -Tussy does not teach the difference of claim 7 of: (the similarity value) must be the same as or greater than (the95 threshold96 value). Tussy of the combination of GRIESER-YOSHIDA -Tussy does teaches the difference of claim 7 of: (the similarity value) must be the same as or greater than (the97 threshold98 value) (or likewise information values being the same as “a first threshold” via: [0027] In one embodiment, this method further comprises capturing supplemental authentication biometric identity information from the user during the authentication session and comparing the supplemental authentication biometric identity information to the authentication biometric identity information. The method also compares the supplemental authentication biometric identity information to the root biometric identity information. The user is authenticated when the comparing determines that the authentication biometric identity information matches the supplemental authentication biometric information within a first threshold, but are not identical, and the comparing determines that the root biometric identity information matches the supplemental authentication biometric information within the predetermined threshold.). It would of been obvious to combine the first threshold for the same reasons as in the rejection of claim 1 with additional Supreme Court steps to those in the rejection of claim 1 . Re 8. (currently amended), GRIESER of the combination of GRIESER,YOSHIDA teaches The method of claim 1, further comprising transmitting (so that “The captured digital image 818 is transmitted to the image processing system 820”) (E) the face derived (A) face feature (B) vector data, (F) the graphic derived (C) face feature (D) vector data, or (G) both to a trusted entity and the trusted entity comparing (via “compares the calculated, depersonalized test data of the document 702 with the image reference data specifically stored for this document in the database 825and obtained from this database.”, pg. 18) (E) the face derived (A) face feature (B) vector data, (F) the graphic derived (C) face feature (D) vector data, or (G) both to a trusted face feature vector stored (“as part of the reference data”, pg. 26, 6th txt blk at the trusted entity. Claim 9 is rejected like claim 1: Re 9. (currently amended), GRIESER of the combination of GRIESER-YOSHIDA -Tussy teaches A system to validate a person’s identity using a graphic a camera configured to: capture at least one facial image of the person, wherein the person is live and physically present in front of the camera (as mapped in the rejection of claim 1); and capture a graphic image of the graphic located on the document; a processor configured to execute machine readable code stored in a non-transitory state on a memory; the memory storing the machine readable code in the non-transitory state, the machine readable code configured to: process the at least one facial image to generate (via fig. 7: arrow) a face (or a “person”-“face”-“data set”, 4th txt blk) derived {{{face vector}}} code (or likewise a “test images BM1-BM5” (Mr. Mustermann: fig. 4A:404)-“derived”-“data”99, machine translation II, pg. 59, 3rd txt blk, as derived encoded information: MRZ symbol “as a vector”, pg. 26, 6th txt blk or “data”100(-set) usually in the singular-verb sense: fig. 7:704), the face derived (vector-data) {{{face vector}}} code representing the person’s face (via data-encoded “image reference data 712”, pg. 25, 8th txt blk: wavy-encoded face lines), but not capable of being reverse processed to generate a face image of the person from which it was derived; process the graphic image to generate a graphic (fig. 7:704: raster-graphic data (encoded) in the singular verb-sense) extracted {{{face vector}}} code, the graphic extracted {{{face vector}}} code (resulting in the encoded face dataset/face image being a “raster graphic”, pg. 13, 4th text blk: fig. 7:704: data (encoded) in the singular verb-sense) representing the person’s face, but not capable of being reverse processed to generate an image of the person from which it was derived; comparing (at test-time) the face derived {{{face vector}}} code (from enrollment) to the graphic extracted {{{face vector}}} code (“recorded again”, pg. 26, 6th txt blk: fig. 7:704 recorded again at test-time) to develop a similarity value, such that the face derived code101 and the graphic extracted code102 represent the person’s face; comparing the similarity value to a first threshold value, and based on the comparing to the first threshold value, generating a validation indicator that represents the likelihood that the graphic extracted face vector code Claim 10 is rejected like claim 2: Re 10. (Original) , GRIESER of the combination of GRIESER,YOSHIDA teaches The system of claim 9 wherein the document comprises one of the following: driver’s license, title of ownership, school transcript, transaction check, identification card, event ticket or voting ballot. Claim 11 is rejected like claim 3: 11. (Currently amended), GRIESER of the combination of GRIESER,YOSHIDA teaches The system of claim 9 wherein the face derived face vector code and the graphic extracted face vector code comprise a string of alpha-numeric values and the graphic extracted face vector code is stored in the graphic. Claim 12 rejected like claim 5: 12. (currently amended). GRIESER of the combination of GRIESER,YOSHIDA teaches The system of claim 9 wherein the machine readable code is further configured to: capture one or more images of a face photograph, asserted to be the person, that is located on the document; process the one or more images of the face photograph to generate (A) a face (&) (B) photograph derived face vector code which is not capable of being reverse processed to generate an image of the person; comparing the (A) face (&) (B) photograph derived face vector code to (C) the face derived face vector code, (D) the graphic extracted face vector code, or (E) both to develop a second similarity value; comparing the second similarity value to the first threshold value or a second threshold value, and based on the comparing, generating a second validation indicator Claim 13 is rejected like claim 8: Re 13. (Currently amended) , GRIESER of the combination of GRIESER,YOSHIDA teaches The system of claim 9 further comprising transmitting the face derived face vector code, the graphic extracted face vector code, or both to a trusted entity and the trusted entity comparing the face derived face vector code, the graphic extracted face vector code, or both to trusted face vector feature codes stored or generated at the trusted entity. Claim 14 is rejected like claims 1 and 9: Re 14. (currently amended), GRIESER and Tussy of the combination of GRIESER-YOSHIDA103-Tussy teaches A method for verifying the validity of an identification document and identity of a person identified by the identification document comprising: capturing one or more images of the graphic on the identification document; processing one or more of the one or more images of the graphic to extract a graphic code, the graphic code comprising data derived from an image of the person’s face, but which cannot be reverse processed to identify the person from which it was derived; transmitting the graphic code to a trusted entity (“to automatically recognize the document ID itself”, pg. 16, 2nd txt blk: fig. 8:820: “Bildbearbeit ungs-system”); {{{at the trusted entity,}}} processing104 the (A) graphic (MRZ) code (symbol) {{{or (B) other (face-image) data}}} sent to the trusted entity to search (“for certain landmarks”, pg. 25, 5th txt blk) for105106 a (C) matching107108 (expressed as “to match… information” (encoded) our way, pg. 3, 3rd txt blk) (&)109 {{{trusted}}}110 (D) {{{face}}}111 (&)112 (E) {{{feature}}}113114 code (only mapped to alternative (C) and not to (D) & (E)), the {{{trusted}}} (D) {{{face}}} (E) {{{feature}}} code comprising data derived from a person’s face, but which cannot be reverse processed to generate an image or likeness of a face from which it was derived115; comparing (A) the graphic code to the {{{trusted}}} (D) {{{face}}} (E) {{{feature}}} code to develop a {{{first}}} similarity value116; capturing one or more images of a face of the person (via Tussy’s fig. 18:1803: “Capture Biometric Data as Enrollment Data” as shown in the 35 USC 103 rejection of claim 1 and reproduced below) presenting the identification document (as initially done at “in-person…passport inspection”, Tussy [0313] penult S, as issued via the 35 USC 103 rejection of claim 1), the person being physically present in front of the camera (as mapped in the rejection of claim 1); processing one or more of the one or more images of the face of the person presenting the identification document to calculate a face derived {{{face vector}}} code (or likewise an “image”-“derived” “biometric identity information”, Tussy [0029] 1st S), the face derived {{{face vector}}} code cannot be reverse processed to identify the person from which it was derived (or likewise “an image of the user cannot be re-created from the root biometric identity information”, Tussy [0029] 2nd S); comparing the graphic (histogram) code (of the 35 USC 103 combination as shown in the rejection of claim 1) to117118 (i.e., with: as shown by the 35 USC 103 combination: combining GREISER with YOSHIDA with Tussy) the (cannot be re-created) face derived {{{face vector}}} code to develop a {{{second}}} similarity value; and providing the {{{first}}} similarity value to a requesting (“test system”, pg. 18, 3rd txt blk) entity119, the requesting entity comprising an entity that is requesting the (“document ID”) verification of the validity of the identification document 120-Tussy: PNG media_image16.png 1894 1063 media_image16.png Greyscale Claim 15 is rejected like claims 2 and 10: Re 15. (original), GRIESER of the combination of GRIESER,YOSHIDA teaches The method of claim 14, wherein the identification document is a driver’s license, passport, or an identification card. Re 16. (original), GRIESER of the combination of GRIESER,YOSHIDA teaches The method of claim 14 wherein the trusted entity is the entity that generated (“in the course of producing (issuing)”, pg. 15, 4th txt blk) the identification document. Claim 17 is rejected like claims 5 and 12: Re 17. (currently amended), GRIESER of the combination of GRIESER-YOSHIDA-Tussy teaches The method of claim 14, wherein the identification document includes a photograph of a face, and the method further comprises: capturing one or more images of the photograph of the face on the identification document with a digital camera; processing (enrolling) the one or more images of the photograph to generate an (F) identification (or “to identify”-“database”121, pg. 4, 7th txt blk) (&) (G) document (&) (H) photograph code, the (F) identification (G) document (H) photograph code is not capable of being reverse processed to generate the face in the photograph; comparing the (F) identification (G) document (H) photograph code to122123 the trusted (D) face (E) feature code to develop a {{{third}}} 124; transmitting the {{{third}}} Re 18. (original), GRIESER of the combination of GRIESER-YOSHIDA-Tussy teaches The method of claim 14 wherein the (A) graphic (MRZ) code includes information (B) from text contained on the identification document or (C) from an identity (“document ID data”, pg. 18, 3rd txt blk) record stored on an identity issuer’s database (825). Conclusion The prior art “nearest to the subject matter defined in the claims” (MPEP 707.05) made of record and not relied upon is considered pertinent to applicant's disclosure. The following table lists several references that are relevant to the subject matter claimed and disclosed in this Application. The references are not relied on by the Examiner, but are provided to assist the Applicant in responding to this Office action: Citation Relevance IDS (8/6/2026) cited Bletsko (Using skin-color motion for 3D face modelling and synthesis) Bletsko teaches a “photograph”125 in the position, role or status of a histogram126-line-graphic which is in turn in the role, function or status of a pencil as the closest to the claimed “the graphic” of claim 1: PNG media_image17.png 849 484 media_image17.png Greyscale IDS (4/17/2025) cited Azanza Ladron et al. (US 10,990,776 B2) Azanza teaches one of claim 1’s Markush alternatives of 2D lines in graphic-form comprising “encoding… face…vector…bits” (implies graphically decoding a face-vector-bits): PNG media_image18.png 609 1069 media_image18.png Greyscale By directly encoding the embedding vector to a downsized resolution, which could be decreased to 2 bytes per component (16 bits float numbers) or even 1 byte per component (8 bits fixed point real numbers). For example, in face biometrics, its 128 embedding vector can be represented using 4096 bits using 4 bytes floats (128×4×8), 2048 bits using 2 bytes floats and 1024 bits using 8 bits fixed point representations. For these cases, a good trade-off between performance and space (which are inversely correlated) seems to exist on the 2 byte-representation per component. By transforming the embedding vector, represented with float numbers, to a compact binary representation through machine learning techniques (i.e.: logistic regression+thresholding). Once a representation of the vector has been obtained (being full, downsized or transformed), it is written in binary format to a machine-readable optical label (like a QR matrix or similar), which is parametrized in terms of size and redundancy, affecting the ability to read the code127 properly and the available data budget to store the biometric embedding vector and any other required information. as the closest to the claimed full Markush alternatives: “extract graphic derived face feature vector data” of claim 1. Medvedev et al. (Towards Facial Biometrics for ID Document Validation in Mobile Devices) PNG media_image19.png 703 1099 media_image19.png Greyscale Medvedev teaches (“life face capture” pg. 5, 3rd para, 3rd S) a trusted front face reference image or a “trusted live captured image of a person from” a camera, pg. 1, 1. Introduction, 3rd para: “Facial recognition technology impacts the overall security, allowing to automate ID document validation. The pipeline of this process usually follows the differential scenario, which implies that, during the verification procedure, the trusted reference is available. As a source of this reference, various systems may use the face image, a template that is previously stored and secured, or the trusted live captured image of a person from the border control camera.” as the closest to the claimed “the person is live and physically present in front of the camera” of claim 1 and teaches “the Graphic Code”, page 8: 4. MRC (Machine Readable Code) Application, 1st para: PNG media_image20.png 440 1070 media_image20.png Greyscale “The match-on-document scenario implies embedding the document sample with additional machine-readable data, which can be implemented in various ways. In our work, we follow the trend to employ computer vision tools to make the document readable with a digital camera. Such an approach maybe conveniently implemented with a machine readable code printed on the surface of the document (see Figure 3). For this work, we utilize the Graphic Code [27] that can be customized for security purposes.” as the closest to the claimed “the graphic code” of claim 1. THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a). A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action. Any inquiry concerning this communication or earlier communications from the examiner should be directed to DENNIS ROSARIO whose telephone number is (571)272-7397. The examiner can normally be reached Monday-Friday, 9AM-5PM EST. Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice. If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Henok Shiferaw can be reached at 571-272-4637. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300. Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000. /DENNIS ROSARIO/Examiner, Art Unit 2676 /Henok Shiferaw/Supervisory Patent Examiner, Art Unit 2676 1 Correspondingly, see below applicant’s remarks (filed 8/6/2026: pages 11,12) regarding a neural network with examiner’s response thereto regarding an inconsistency of Markush alternatives. 2 proprietary: (of a brand name, product, service, formula, etc.) protected by a patent, copyright, or trademark., wherein brand name is defined: a product, line of products, or service bearing a widely known brand name, wherein know is defined: be acquainted with (a thing, place, person, etc.), as by sight, experience, or report., wherein experience is defined: knowledge or practical wisdom gained from what one has observed, encountered, or undergone. (Dictionary.com) 3 “stored inside the graphic code” maps to claim 3’s (US 2021/0011986 A1): 3. The method of claim 1, wherein the first face-derived feature vector data and the second face-derived feature vector data comprise a string of alpha and numeric values that are encoded and stored in the graphic. 4 This limitation maps to the beginning of claim 1 of US 2021/0011986 A1 5 Claim 9 is rejected like claim 1 of US 2021/0011986 A1 6 This limitation maps to the beginning of claims 1 and 9 7 Thus “where” clause is not taught 8 single {curly brackets} map to a corresponding set(s) of single curly brackets in the other claim 9 double {{curly brackets}} map to a corresponding set(s) of double-curly brackets in another claim (both claim 1s): Thus claim 9 should be mapped to claim 1. 10 35 USC 103 DIFFERENCE: This “comparing” limitation is a difference under 35 USC 103 11 Claim 9 is rejected like claim 1 of US 2021/0011986 A1 12 This limitation maps to the beginning of claims 1 and 9 13 Thus “where” clause is not taught 14 This limitation maps to the other claim with same number of brackets. 15 This curly brackets map to a corresponding set(s) number of curly brackets in the other claim 16 The limitation in brackets is mapped to the same number of brackets in claim 1 of US 2021/0011986 A1. 17 Claim 12 is rejected like claim 1 18 Claim 14 is mapped to claim 1, below 19 This “transmitting” limitation maps to claim 8’s “transmitting the first face-derived feature vector data, the second face-derived feature vector data, and the graphic derived feature vector data to a trusted entity” and to claim 18’s “transmitting the second similarity value to a requesting entity.” 20 35 USC 103 DIFFERENCE: This difference --“at the trusted entity” limitation-- maps to clams 8 and 13: thus claim 14 needs to be mapped to claim 1,8 or 9,13. 21 35 USC 103 DIFFERENCE: This difference “first” of “a first similarity value” is another difference under 35 USC 103. 22 This “comparing” limitation in single-brackets maps to single-brackets further below in claim 14 of US 2021/0011986 A1 23 {{{{{This 5 bracket limitation}}}}} maps to claim 14 of US 2021/0011986 A1 above 24 This “providing” limitation maps to claim 20 of US 2021/0011986 A1 25 Claim 14 is rejected like claim 1 26 This “transmitting” limitation maps to claim 8’s (US 20260024378 A1) “transmitting the first face-derived feature vector data, the second face-derived feature vector data, and the graphic derived feature vector data to a trusted entity” and to claim 18’s “transmitting the second similarity value to a requesting entity.” 27 35 USC 103 DIFFERENCE: This “at the trusted entity” limitation is a difference under 35 USC 103. 28 These four single bracket limitations to four-bracket limitations of claim 1 of US 2021/0011986 A1 29 35 USC 103 DIFFERENCE: This “providing” limitation maps to claim 20 of US 2021/0011986 A1 that depends on claim 14, not claim 1, of US 2021/0011986 A1 30 Claim 16 maps to claims 6,13 31 Claim 16 maps to claims 6,13 32 This three-bracket limitation of claim 14 maps to a corresponding three-bracket in claim 1 of US 2026/0024378 A1 33 Claim 18 maps to claim 17 34 {{{{{{{{This}}}}}}}} maps to claim 17 35 This} maps to claim 17 36 compare: to examine (two or more objects, ideas, people, etc.) in order to note similarities and differences. (Dictionary.com) 37 similarity: the state of being similar; likeness; resemblance. (Dictionary.com) 38 and: (used to connect [Markush] alternatives). (Dictionary.com) 39 “arranged”: MPEP 2152.02 Prior Art Under AIA 35 U.S.C. 102(a)(1) (Patented, Described in a Printed Publication, or in Public Use, on Sale, or Otherwise Available to the Public) [R-08.2017] 2152.02(b) Described in a Printed Publication [R-11.2013], 3rd para, reproduced below. 40 of: (used to indicate possession, connection, or association). (Dictionary.com) 41 Examiner’s notes that Claim 1 as amendment makes this clear 42 Examiner notes that Claim 1 claims this in full Markush alternatives (of coordinate-adjectives) as “the graphic derived face feature vector data”, wherein “graphic derived” and “face” and “feature” and “vector” are interpreted as coordinate-adjectives relative to “data”, wherein coordinate is defined: Grammar. of the same rank in grammatical construction, as Jack and Jill in the phrase Jack and Jill, or got up and shook hands in the sentence He got up and shook hands, wherein rank is defined: relative position or standing. (Dictionary.com) 43 Examiner notes that applicants have picked/elected the Markush alternative “face data” of the full Markush alternatives as “the graphic derived face feature vector data”. 44 The examiner will map the art to the Markush alternative: “face data”. 45 Examiner notes that Claim 1 claims this in full Markush alternatives as “the graphic derived face feature vector data”. 46 between: in comparing. (Dictionary.com) 47to: (used for expressing addition or accompaniment) with. (Dictionary.com) 48 to: (used for expressing comparison or opposition). (Dictionary.com) 49 to: as compared with, as against (Dictionary.com) 50 Applicant’s disclosure [0161] leaves open-ended the grammatical sense/form/meaning of “to” as “Numerous modifications”. Thus I interpret this particular “to” (claim 1, line 13: “data to the graphic”) as modifier to mean: (used for expressing addition or accompaniment) with. (Dictionary.com) 51 Note that claim 1, line 8’s “the graphic” is objected for missing the article “a” as in “a printed graphic”. 52 POSITIVE STATEMENT: Applicant’s remarks about the neural-network vector being non-reverse-processed is the novelty of applicant’s invention about the claimed validating a person identity: applicant’s disclosure at [0447] is a neural network fix to a face-decrypting problem [0446]. 53 “vector” used as an adjective describing the noun “data” 54 “vector” used as an adjective describing the noun “data” 55 “vector” used as a noun possessing a “face” attribute describing the noun “vector” 56 “feature” is an adjective describing “vector” 57 “vector” is a noun described by the adjective “feature” 58 thereon: on or upon that or it. (Dictionary.com): deletion of “an item, having a graphic thereon” made the claim form (such as --a cup of water on the table-- or --on the rocks--, wherein “on” in various contexts is understood to be placed at a position facing upward otherwise the water/ice cubes will spill out of the cup, wherein “on the rocks” is defined: Served over ice only, as in He always drinks whiskey on the rocks . The “rocks” here are the ice cubes. [Mid-1900s] (Dictionary.com)) of the claimed “on” (at claim 1, line 8: “on the item”) broader or read in more dictionary senses of “on”, wherein form is defined: Grammar. a word, part of a word, or group of words (“an item, having a graphic thereon”) forming a construction that recurs in various contexts in a language with relatively constant meaning (dictionary sense). (Dictionary.com) 59 person: the actual self or individual personality of a human being, wherein self is defined: a person or thing referred to with respect to complete individuality, wherein individuality is defined: the particular character, or aggregate of qualities, that distinguishes one person or thing from others; sole and personal nature, wherein distinguish is defined: to recognize as distinct or different; recognize the salient or individual features or characteristics of, wherein recognize is defined: to identify as something or someone previously seen, known, etc.., wherein identify is defined: to recognize or establish as being a particular person or thing; verify the identity of. (Dictionary.com) 60 Markush element of coordinate-adjective Markush alternatives follow: [(A) & (B)], wherein coordinate is defined: Grammar. of the same rank in grammatical construction, as Jack and Jill in the phrase Jack and Jill, or got up and shook hands in the sentence He got up and shook hands, wherein rank is defined: a class in any scale of comparison, wherein class is defined: Grammar. form class, wherein form class is defined: Grammar. a class of words or forms in a given language that have one or more grammatical features in common, as, in Latin, all masculine nouns (feature & vector) in the nominative singular, all masculine singular nouns (feature & vector), all masculine nouns (feature & vector), or all nouns (feature & vector). 61 “face derived” is a cumulative adjective 62 specific: peculiar or proper to somebody or something, as qualities, characteristics, effects, etc.., wherein characteristic is defined: a distinguishing feature or quality. (Dictionary.com) 63 Since GRIESER teaches coordinate-adjective Markush alternative (A), the Markush element [(A) & (B)] is taught under the broadest reasonable interpretation of claim 1 64 coordinate adjective test: data is a vector & feature or data is a feature & a vector: same 65 graph: a diagram representing a system of connections or interrelations among two or more things by a number of distinctive dots, lines, bars, etc., wherein represent is defined: to express or designate by some term, character, symbol, or the like, wherein character is defined: Computers. a. any symbol, as a number, letter, punctuation mark, etc., that represents data and that, when encoded, is usable by a machine. b. one of a set of basic symbols that singly or in a series of two or more represents data and, when encoded, is usable in a computer, wherein encode is defined: to convert (a message, information, etc.) into code. (Dictionary.com) 66 Regarding “on” in view of applicant’s disclosure: --[0161]Numerous modifications may be made to the above system and method without departing from the scope of the invention. For example, the images may be processed by a face matching algorithm on the device and may also be converted to biometric data on the device which is then compared to previously created biometric data for an authorized user. Alternatively, the images from a device may be sent through a wired or wireless network where the face matching algorithms running on a separate server can process the images, create biometric data, and compare that data against previously stored data that assigned to that device.—wherein modifications is defined: an act or instance of modifying, wherein modify is defined: to change somewhat the form or qualities of; alter partially; amend, wherein form is defined: Grammar. a word, part of a word, or group of words forming a construction that recurs in various contexts in a language with relatively constant meaning. (Dictionary.com) 67 on: in connection, association, or cooperation with; as a part or element of. (Dictionary.com) 68 the: (used, especially before a noun, with a specifying or particularizing effect, as opposed to the indefinite or generalizing force of the indefinite article a or an ). (Dictionary.com) 69 graphic: of or relating to the graphic arts, wherein graphic arts is defined: the arts of drawing, painting, and printmaking, wherein drawing is defined: a graphic representation by lines of an object or idea, as with a pencil; a delineation of form without reference to color, wherein representation is defined: the expression or designation by some term, character, symbol, or the like, wherein character is defined: Computers. a. any symbol, as a number, letter, punctuation mark, etc., that represents data and that, when encoded, is usable by a machine. b. one of a set of basic symbols that singly or in a series of two or more represents data and, when encoded, is usable in a computer, wherein encode is defined: to convert (a message, information, etc.) into code. (Dictionary.com) 70 machine-readable: Computers. of or relating to data encoded on an appropriate medium and in a form suitable for processing by computer. (Dictionary.com) 71 Since GRISER teaches coordinate-adjective Markush alternative (E): graphic data, the Markush element [(E) & (F) &(G) & (H)] is taught under the broadest reasonable interpretation of claim 1 72 reference: a book or other source of useful facts or information, such as an encyclopedia, dictionary, etc., wherein fact is defined: a truth known by actual experience or observation; something known to be true, wherein true is defined: being or reflecting the essential or genuine character (i.e., a distinguishing feature) of something. (Dictionary.com) 73 Since GRIESER teaches Markush alternative (C), [(C) & (D)] is taught under the broadest reasonable interpretation of claim 1 74 detect: to extract information from (an electromagnetic wave) (Dictionary.com) 75bin: a box or enclosed place for storing grain, coal, or the like, wherein enclosed is defined: to shut or hem in; close in on all sides, wherein in is defined: on the inside; within. (Dictionary.com) 76 The text in {{{triple curly brackets}}} in the claim set “is taught by the prior art” via MPEP 2143 All Claim Limitations Must Be Considered [R-01.2024] As a general matter, the grammar (coordinate adjectives: e.g., “face derived face feature vector”) and ordinary meaning of terms as understood by one having ordinary skill in the art used in a claim will dictate whether, and to what extent, the language limits the claim scope. Language (coordinate adjectives: e.g., “face derived face feature vector”) that suggests or makes a feature or step optional but does not require that feature or step does not limit the scope of a claim under the broadest reasonable claim interpretation. In addition, when a claim requires selection of an element from a list (coordinate adjectives: e.g., “face derived face feature vector”) of alternatives, the prior art teaches the element if one of the alternatives is taught by the prior art. See, e.g., Fresenius USA, Inc. v. Baxter Int’l, Inc., 582 F.3d 1288, 1298, 92 USPQ2d 1163, 1171 (Fed. Cir. 2009). 77 Regarding “to” in view of applicant’s disclosure: --[0161]Numerous modifications may be made to the above system and method without departing from the scope of the invention. For example, the images may be processed by a face matching algorithm on the device and may also be converted to biometric data on the device which is then compared to previously created biometric data for an authorized user. Alternatively, the images from a device may be sent through a wired or wireless network where the face matching algorithms running on a separate server can process the images, create biometric data, and compare that data against previously stored data that assigned to that device.—wherein modifications is defined: an act or instance of modifying, wherein modify is defined: to change somewhat the form or qualities of; alter partially; amend, wherein form is defined: Grammar. a word, part of a word, or group of words forming a construction that recurs in various contexts in a language with relatively constant meaning. (Dictionary.com) 78 to: (used for expressing addition or accompaniment) with. (Dictionary.com) 79 exact: precise, as opposed to approximate, wherein precise is defined: definitely or strictly stated, defined, or fixed, wherein defined is defined: to fix or lay down clearly and definitely; specify distinctly, wherein definitely is defined: in a clear and definite manner; unambiguously, wherein definite is defined: positive; certain; sure, wherein certain is defined: that may be depended on; trustworthy; unfailing; reliable, wherein trustworthy is defined: deserving of trust or confidence; dependable; reliable, wherein trust is defined: confident expectation of something; hope, wherein expectation is defined: the degree of probability that something will occur, wherein probability is defined: a strong likelihood or chance of something. (Dictionary.com) 80 similarity: the state of being similar; likeness; resemblance, wherein likeness is defined: the state or fact of being like, wherein like is defined: corresponding or agreeing in general or in some noticeable respect; similar; analogous, wherein corresponding is defined: associated in a working or other relationship (Dictionary.com). 81 person: the actual self or individual personality of a human being, wherein self is defined: a person or thing referred to with respect to complete individuality, wherein individuality is defined: the particular character, or aggregate of qualities, that distinguishes one person or thing from others; sole and personal nature, wherein distinguish is defined: to recognize as distinct or different; recognize the salient or individual features or characteristics of, wherein recognize is defined: to identify as something or someone previously seen, known, etc.., wherein identify is defined: to recognize or establish as being a particular person or thing; verify the identity of. (Dictionary.com) 82 (italics) represent claim limitations already taught 83 Ellipsis (…) represent claim limitations already taught 84 (italics) represent claim limitations already taught 85 ellipses (…) represent claim limitations already taught 86 person: the actual self or individual personality of a human being, wherein self is defined: a person or thing referred to with respect to complete individuality, wherein individuality is defined: the particular character, or aggregate of qualities, that distinguishes one person or thing from others; sole and personal nature, wherein distinguish is defined: to recognize as distinct or different; recognize the salient or individual features or characteristics of, wherein recognize is defined: to identify as something or someone previously seen, known, etc.., wherein identify is defined: to recognize or establish as being a particular person or thing; verify the identity of. (Dictionary.com) 87 (italics) represent claim limitations already taught 88 Ellipsis (…) represent claim limitations already taught 89 person: the actual self or individual personality of a human being, wherein self is defined: a person or thing referred to with respect to complete individuality, wherein individuality is defined: the particular character, or aggregate of qualities, that distinguishes one person or thing from others; sole and personal nature, wherein distinguish is defined: to recognize as distinct or different; recognize the salient or individual features or characteristics of, wherein recognize is defined: to identify as something or someone previously seen, known, etc.., wherein identify is defined: to recognize or establish as being a particular person or thing; verify the identity of. (Dictionary.com) 90 (italics) represent claim limitations already taught 91 Ellipsis (…) represent claim limitations already taught 92 “the threshold value” is interpreted as “the first threshold value”. 93 BROAD CLAIM LANGUAGE: threshold: a level or point at which something would happen, would cease to happen, or would take effect, become true, etc (Dictioanry.com) 94 person: the actual self or individual personality of a human being, wherein self is defined: a person or thing referred to with respect to complete individuality, wherein individuality is defined: the particular character, or aggregate of qualities, that distinguishes one person or thing from others; sole and personal nature, wherein distinguish is defined: to recognize as distinct or different; recognize the salient or individual features or characteristics of, wherein recognize is defined: to identify as something or someone previously seen, known, etc.., wherein identify is defined: to recognize or establish as being a particular person or thing; verify the identity of. (Dictionary.com) 95 “the threshold value” is interpreted as “the first threshold value”. 96 BROAD CLAIM LANGUAGE: threshold: a level or point at which something would happen, would cease to happen, or would take effect, become true, etc (Dictioanry.com) 97 “the threshold value” is interpreted as “the first threshold value”. 98 BROAD CLAIM LANGUAGE: threshold: a level or point at which something would happen, would cease to happen, or would take effect, become true, etc (Dictioanry.com) 99 data: (usually used with a singular verb) information in digital format, as encoded text or numbers, or multimedia images, audio, or video. (Dictionary.com) 100 data: (usually used with a singular verb) information in digital format, as encoded text or numbers, or multimedia images, audio, or video. (Dictionary.com) 101 Applicant’s have elected (as well as the examiner) by amendment the Markush alternative as the claimed “face derived code” 102 Applicant’s have elected (as well as the examiner) by amendment the Markush alternative as the claimed “graphic extracted code”. 103 YOSHIDA’s teachings are not directly mapped to claim 14, rather GRIESER’s and Tussy’s are. 104 Markush element of Markush alternatives follows: [(A) or (B)] 105 for: intended to belong to, or be used in connection with. (Dictionary.com) 106 Markush element of coordinate Markush alternatives follows: [(C) & (D) & (E)]. 107 coordinate adjective 108 BROAD CLAIM LANGUAGE: -ing (of “matching”): a suffix of nouns formed from verbs, expressing the action of the verb or its result, product, material, etc. {GRIESER saying that a comparison match does not work this way but our comparison information way works this way} (the art of building; a new building; cotton wadding ). (Dictionary.com) 109 coordinate adject test: code is a trusted face & a trusted feature & a matching (noun-form): it makes sense 110 cumulative adjective 111 coordinate adjective 112 coordinate adjective test 113 coordinate adjective 114 Since GRISER teaches Markush alternative (C), the Markush element [(C) & (D) & (E)] is taught under the broadest reasonable interpretation of claim 14 115 This limitation is directed to Markush limitation (D)(E) that is already taught since Markush (C) is already taught 116 This limitation is directed to Markush limitation (D)(E) that is already taught since encoded- information-matching our-way Markush alternative (C) is already taught 117 Regarding “to” in view of applicant’s disclosure: --[0161]Numerous modifications may be made to the above system and method without departing from the scope of the invention. For example, the images may be processed by a face matching algorithm on the device and may also be converted to biometric data on the device which is then compared to previously created biometric data for an authorized user. Alternatively, the images from a device may be sent through a wired or wireless network where the face matching algorithms running on a separate server can process the images, create biometric data, and compare that data against previously stored data that assigned to that device.—wherein modifications is defined: an act or instance of modifying, wherein modify is defined: to change somewhat the form or qualities of; alter partially; amend, wherein form is defined: Grammar. a word, part of a word, or group of words forming a construction that recurs in various contexts in a language with relatively constant meaning. (Dictionary.com) 118 to: (used for expressing addition or accompaniment) with. (Dictionary.com) 119 This limitation is directed to Markush limitation (D)(E) that is already taught since encoded- information-matching our-way Markush alternative (C) is already taught 120 YOSHIDA’s teachings are not directly mapped to claim 14, rather GRIESER’s and Tussy’s are. 121 database: a comprehensive collection of related data datum organized for convenient access, generally in a computer, wherein data is defined: (usually used with a singular verb) information in digital format, as encoded text or numbers, or multimedia images, audio, or video. (Dictionary.com) 122 CLAIM SCOPE regarding “to”, applicant’s disclosure: --Adaptations and modifications [0161]Numerous modifications may be made to the above system and method without departing from the scope of the invention.—wherein scope is defined: Linguistics, Logic. the range of words (one of which is “code”) or elements of an expression (claims 14 & 17) over which a modifier (a patent examiner) or operator (or me) has control. (Dictionary.com) 123 to: (used for expressing addition or accompaniment) with. (Dictionary.com): a prepositional modifier 124 This limitation is directed to Markush limitation (D)(E) that is already taught since encoded- information-matching our-way Markush alternative (C) is already taught 125 photograph: a picture produced by photography, wherein picture is defined: a visual representation of a person, object, or scene, as a painting, drawing, photograph, etc.., wherein drawing is defined: a graphic representation by lines of an object or idea, as with a pencil; a delineation of form without reference to color. (Dictionary.com) 126 The word “histogram” is mapped in the 35 USC 103 rejection of claim 1 127 QR code: the brand name for a matrix barcode that is read by photographing it with the camera of a smartphone or other mobile device that is equipped with a 2D barcode reader, wherein barcode is defined: a series of lines of varying width, printed, as on a container or product, that can be read by an optical scanner to determine charges for purchases, destinations for letters, etc., wherein printed is defined: Computers. to produce (data) in legible alphanumeric or graphic form. (Dictionary.com)