DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 09/20/2024 have been considered by the examiner and been placed of record in the file.
Allowable Subject Matter
Claims 26-27, 33-34 and 40 would be allowable if rewritten to overcome the double patenting rejection, set forth in this Office action and to include all of the limitations of the base claim and any intervening claims.
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 obviousness-type double patenting rejection is appropriate where the conflicting claims 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 conflicting 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.
Effective January 1, 1994, a registered attorney or agent of record may sign a terminal disclaimer. A terminal disclaimer signed by the assignee must fully comply with 37 CFR 3.73(b).
Claims 21-25, 28-32 and 35-39 are rejected on the ground of nonstatutory obviousness-type double patenting as being unpatentable over claims 1-20 of U.S. Patent Application No. 17/037,629. Although the conflicting claims are not identical, they are not patentably distinct from each other because the claims scopes are identical.
Instant application
Application 17/037,629
Claim 21. An apparatus comprising:
interface circuitry;
machine-readable instructions; and
at least one processor circuit to be programmed by the machine-readable instructions to:
determine an image quality classification of input media;
determine a Gabor filter classification of the input media;
determine a local binary pattern classification of the input media;
generate a score based on the image quality classification, the Gabor filter classification, and the local binary pattern classification; and
determine whether the input media is a deepfake based on the score.
Claim 1. An apparatus to determine whether input media is authentic, the apparatus comprising:
a classifier to generate a first probability based on a first output of a local binary model manager,
a second probability based on a second output of a filter model manager, and
a third probability based on a third output of an image quality assessor; and
a score analyzer to:
obtain the first, second, and third probabilities from the classifier; and
in response to obtaining a first result and a second result,
generate a score indicative of whether the input media is authentic based on the first result, the second result, the first probability, the second probability, and the third probability.
37,629.The two independent claims , 21 and 1, of the instant and parent respectively are shown side by side. It is clear that in both cases the idea is related to detecting whether an input media is fake (i.e. authentic or not as in parent case). The parent case (17/037,629) discloses 3 different probabilities which are equivalent to quality classification, Gabor filter classification and local binary pattern classification. This is conclusion is based on the fact that the three probabilities disclosed in the parent case are not explicitly defined. Consequently, the three determinations disclose in the instant application can be interpreted as probabilities.
Similar analysis can be applied to claims 28 of instant case and 8 of case 17/037,629. Also between 35 and 15 of instant and parent case respectively.
Dependent claims:
Claim 22; all limitations can be obtained from claim 2 of case 17/037,629.
Claim 23; all limitations can be obtained from claim 2 of case 17/037,629.
Claim 24; all limitations can be obtained from claim 3 of case 17/037,629.
Claim 25; all limitations can be obtained from claim 3 of case 17/037,629.
Claim 29; all limitations can be obtained from claim 9 of case 17/037,629.
Claim 30; all limitations can be obtained from claim 9 of case 17/037,629.
Claim 31; all limitations can be obtained from claim 11 of case 17/037,629.
Claim 32; all limitations can be obtained from claim 10 of case 17/037,629.
Claim 36; all limitations can be obtained from claim 16 of case 17/037,629.
Claim 37; all limitations can be obtained from claim 16 of case 17/037,629.
Claim 38; all limitations can be obtained from claim 17 of case 17/037,629.
Claim 39; all limitations can be obtained from claim 18 of case 17/037,629.
It would have been obvious to a person of ordinary skill in the art, at the time the invention was made to use claims of US Patent Application No. 17/037,629 to provide all the functions of the current application.
Similar analysis applies to application 18/340,013.
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.
Claims 21-23, 28-30 and 35-37 are rejected under 35 U.S.C. 103 as being unpatentable over Kim et al. (US 2013/0163829 A) in view of De Brouwer (US 20180289334 A1).
Claim 21. Kim et al. disclose An apparatus (read as computer system [0003]) comprising:
interface circuitry (read as computer [0103]. Computers include interface circuitry);
machine-readable instructions (read as program instructions that can be executed by computers, and may be recorded in computer readable media [0103]); and
at least one processor circuit to be programmed by the machine-readable instructions (read as program instructions that can be executed by computers, and may be recorded in computer readable media [0103]) to:
determine an image quality classification of input media (read as The extractor 340 may generate an optimal face graph using the normalized rectangular facial area [0092]);
determine a Gabor filter classification of the input media (read as extract a Gabor feature value and a position value from the generated optimal face graph [0092]);
determine a local binary pattern classification of the input media (read as the detector 320 may detect a plurality of facial areas with a predetermined (nxn) size from the input facial image using the Adaboost algorithm, average coordinate values of the plurality of detected facial areas [0090]);
generate a score based on the image quality classification, the Gabor filter classification, and the local binary pattern classification (read as the extracted Gabor feature value and position value of each of nodes of the optimal face graph as an input value of the SVM classifier and as a result, may obtain an output value of the SVM classifier [0096]); and
determine whether the input media is a deepfake based on the score (read as may determine whether the input facial image is a normal facial image or a facial image disguised with a mask or sunglasses using the obtained output value and a pre-generated optimal classification plane [0096]).
The combined teaching of multiple embodiment, FIG. 1-9, disclosed by Kim et al. was used in the rejection. It is clear that Kim et al. disclose the idea of detecting a fake/disguised human face.
Therefore, it would have been obvious to a person of ordinary skill in the art, at the time the invention was filed, to use the teaching of Kim et al. in order to realize all limitation of the claim invention namely the idea of providing an algorithm that may accurately detect a facial area and determine whether a facial image is disguised using the detection result even though a portion of the facial area is occluded with sunglasses or a mask (Kim et al. [0008]).
Claim 22. The apparatus of claim 21, Kim et al. disclose,
wherein the input media is classified as deepfake when the score is beneath a threshold (read as determine whether an input facial image sample is disguised using the obtained output value [0102]. Also FIG. 7).
Claim 23. The apparatus of claim 22, Kim et al. disclose,
wherein the input media is classified as authentic when the score is above the threshold (read as determine whether an input facial image sample is disguised using the obtained output value [0102]. Also FIG. 7).
Claim 28. Kim et al. disclose At least one non-transitory machine-readable medium comprising machine- readable instructions to cause at least one processor circuit (read as program instructions that can be executed by computers, and may be recorded in computer readable media [0103]) to at least:
determine an image quality classification of input media (read as The extractor 340 may generate an optimal face graph using the normalized rectangular facial area [0092]);;
determine a Gabor filter classification of the input media (read as extract a Gabor feature value and a position value from the generated optimal face graph [0092]);
determine a local binary pattern classification of the input media (read as the detector 320 may detect a plurality of facial areas with a predetermined (nxn) size from the input facial image using the Adaboost algorithm, average coordinate values of the plurality of detected facial areas [0090]);;
generate a score based on the image quality classification, the Gabor filter classification, and the local binary pattern classification (read as the extracted Gabor feature value and position value of each of nodes of the optimal face graph as an input value of the SVM classifier and as a result, may obtain an output value of the SVM classifier [0096]); and
determine whether the input media is a deepfake based on the score (read as may determine whether the input facial image is a normal facial image or a facial image disguised with a mask or sunglasses using the obtained output value and a pre-generated optimal classification plane [0096]).
The combined teaching of multiple embodiment, FIG. 1-9, disclosed by Kim et al. was used in the rejection. It is clear that Kim et al. disclose the idea of detecting a fake/disguised human face.
Therefore, it would have been obvious to a person of ordinary skill in the art, at the time the invention was filed, to use the teaching of Kim et al. in order to realize all limitation of the claim invention namely the idea of providing an algorithm that may accurately detect a facial area and determine whether a facial image is disguised using the detection result even though a portion of the facial area is occluded with sunglasses or a mask (Kim et al. [0008]).
Claim 29. The at least one non-transitory machine-readable medium of claim 28, Kim et al. disclose,
wherein the input media is classified as deepfake when the score is beneath a threshold (read as determine whether an input facial image sample is disguised using the obtained output value [0102]. Also FIG. 7).
Claim 30. The at least one non-transitory machine-readable medium of claim 29, Kim et al. disclose,
wherein the input media is classified as authentic when the score is above the threshold (read as determine whether an input facial image sample is disguised using the obtained output value [0102]. Also FIG. 7).
Claim 35. Kim et al. disclose A method (read as a method for recognizing a disguised face [0002]) comprising:
determining an image quality classification of input media (read as The extractor 340 may generate an optimal face graph using the normalized rectangular facial area [0092]);
determining a Gabor filter classification of the input media (read as extract a Gabor feature value and a position value from the generated optimal face graph [0092]);
determining a local binary pattern classification of the input media (read as the detector 320 may detect a plurality of facial areas with a predetermined (nxn) size from the input facial image using the Adaboost algorithm, average coordinate values of the plurality of detected facial areas [0090]);
generating, by at least one processor circuit programmed by at least one instruction, a score based on the image quality classification, the Gabor filter classification, and the local binary pattern classification (read as the extracted Gabor feature value and position value of each of nodes of the optimal face graph as an input value of the SVM classifier and as a result, may obtain an output value of the SVM classifier [0096]); and
determining, by one or more of the at least one processor circuit, whether the input media is a deepfake based on the score (read as may determine whether the input facial image is a normal facial image or a facial image disguised with a mask or sunglasses using the obtained output value and a pre-generated optimal classification plane [0096]).
The combined teaching of multiple embodiment, FIG. 1-9, disclosed by Kim et al. was used in the rejection. It is clear that Kim et al. disclose the idea of detecting a fake/disguised human face.
Therefore, it would have been obvious to a person of ordinary skill in the art, at the time the invention was filed, to use the teaching of Kim et al. in order to realize all limitation of the claim invention namely the idea of providing an algorithm that may accurately detect a facial area and determine whether a facial image is disguised using the detection result even though a portion of the facial area is occluded with sunglasses or a mask (Kim et al. [0008]).
Claim 36. The method of claim 35, Kim et al. disclose,
wherein the input media is classified as deepfake when the score is beneath a threshold (read as determine whether an input facial image sample is disguised using the obtained output value [0102]. Also FIG. 7).
Claim 37. The method of claim 36, Kim et al. disclose,
wherein the input media is classified as authentic when the score is above the threshold (read as determine whether an input facial image sample is disguised using the obtained output value [0102]. Also FIG. 7).
1. - 20. (Cancelled)
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Refer to PTO-892.
Prior art included in PTO-892 discloses ideas related to the claimed invention. In this regard Chang et al. (CN 108960201 A) discloses steps of identifying a human face based on facial key point extraction and sparse representation classification, comprising the steps of FIG. 1.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MOHAMMED RACHEDINE whose telephone number is (571)272-9249. The examiner can normally be reached Mon-Fri 8-5.
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, Jeanette J. Parker can be reached at (571)270-3647. 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.
MOHAMMED . RACHEDINE
Examiner
Art Unit 2649
/MOHAMMED RACHEDINE/Primary Examiner, Art Unit 2646
Prosecution Insights