DETAILED ACTION
Notice of Pre-AIA or AIA Status
1. The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Priority
2. Receipt is acknowledged of certified copies of papers required by 37 CFR 1.55.
Drawings
3. The drawings were received on January 7, 2026. These drawings are acceptable.
Specification
4. The amendments to the specification were received on January 7, 2026. The specification is acceptable.
Response to Amendment
5. The amendment filed January 7, 2026 has been entered. Claims 1-11 remain pending in the application. Applicant’s amendments to the Specification, Drawings, and Claims have overcome each and every objection. Applicant’s amendments to the Claims have also overcome the 35 U.S.C. 101 and 112(b) rejections previously set forth in the Non-Final Office Action mailed August 8, 2025. The claims are also no longer interpreted under 35 U.S.C. 112(f) interpretation.
Response to Arguments
6. Applicant's arguments filed January 7, 2026 have been fully considered but they are not persuasive.
7. Applicant argues that Im (Japanese Patent Application Publication No. 2013-205071 A -- IDS) fails to disclose performing efficient inspection while preserving confidential information by performing learning within the site containing the surfaces to be inspected. The Applicant argues that Im does not disclose the appearance inspection apparatus performing learning within the site containing the surfaces to be inspected and thus does not teach preserving confidential information while performing appearance inspection.
Examiner replies that 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., "performing learning within the site containing the surfaces to be inspected" and "preserving confidential information while performing appearance inspection") 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).
Furthermore, Applicant’s arguments with respect to claim(s) 1, 9, and 11 have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
Alasia et al. (U.S. Patent Application Publication No. 2008/0267514 A1) in Paragraph 17 discloses performing image processing on-site.
Thus, the amended claim 1, 9, 11 and their dependents stand rejected.
8. Conclusion: The rejections set in the previous Office Action are shown to have been proper, and the claims are rejected below. New citations and parenthetical remarks can be considered new grounds of rejection and such new grounds of rejection are necessitated by the Applicant’s amendments to the claims. Therefore, the present Office Action is made final.
Claim Objections
9. Claim 1 objected to because of the following informalities: "learned execution selection information" on line 13 and 19-20 should be “training execution selection information” to be consistent with terminology with the Specification Paragraph 12. Appropriate correction is required.
10. Claim 9 objected to because of the following informalities: "learned execution selection information" on line 14 and 20-21 should be “training execution selection information” to be consistent with terminology with the Specification Paragraph 12. Appropriate correction is required.
11. Claim 11 objected to because of the following informalities: "learned execution selection information" on line 12 and 18-19 should be “training execution selection information” to be consistent with terminology with the Specification Paragraph 12. Appropriate correction is required.
Claim Rejections - 35 USC § 112
12. The following is a quotation of the first paragraph of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
The following is a quotation of the first paragraph of pre-AIA 35 U.S.C. 112:
The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor of carrying out his invention.
13. Claims 1, 9, and 11 are rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the written description requirement. The claim(s) contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for applications subject to pre-AIA 35 U.S.C. 112, the inventor(s), at the time the application was filed, had possession of the claimed invention.
Claim 1 line 14, Claim 9 line 15, and Claim 11 line 13 “perform learning based on the prestored normal picture” is not supported by the Applicant’s Specification. The Applicant’s specification does not mention performing learning or training used the prestored normal picture. The Applicant’s Specification in Paragraphs 6, 14, and 16 only discloses performing the anomaly detection with the prestored normal picture, not the learning. The Applicant is advised to change “prestored” with “prescribed” to have support through Paragraph 12 of the Applicant’s Specification.
Claims 2-8 and 10 are rejected by dependency on Claim 1, 9, and 11.
The claims will be examined as best understood by the Examiner.
Claim Rejections - 35 USC § 103
14. In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
15. The text of those sections of Title 35, U.S. Code not included in this action can be found in a prior Office action.
16. Claim(s) 1-3 and 8-11 is/are rejected under 35 U.S.C. 103 as being unpatentable over Im (Japanese Patent Application Publication No. 2013-205071 A -- IDS) in view of Nakagawa (WIPO Patent Application Publication No. 2020/071162 A1 -- IDS) and Alasia et al. (U.S. Patent Application Publication No. 2008/0267514 A1), hereinafter referred to as Alasia.
17. Regarding claim 1, Im teaches an anomaly display device comprising a processor configure to execute a program to (Paragraph 31 teaches a control unit that is a general-purpose computer and equipped with a CPU that executes functions):
acquire starting information including information for starting an anomaly detection for detecting an anomaly in an image included in an input picture (Paragraphs 35-36 teach a device that acquires information about the distance data of the object or substrate in order to start the process of taking photos for anomaly detection. This information can be considered part of the starting information; Paragraph 40 teaches starting the inspection or anomaly detection using information, or starting information, that includes controlling the XY movement to inspect the entire object. Thus, the starting information is acquired to start anomaly detection);
acquire the input picture (Paragraph 29 teaches a camera that can capture an image of the object; Paragraph 40 teaches capturing images of the object with a camera; Paragraph 52 teaches the optical image inspection means acquires the input image from the second storage in order to start the anomaly detection. The optical image inspection means can be considered the input picture acquisition unit);
execute the anomaly detection, based on the acquired starting information, by comparing the acquired input picture with information based on a prestored normal picture (Paragraph 52 teaches comparing pixels in the color image data to the data in a master image. The master image can be considered a prestored normal picture and its data is the information based on a prestored normal picture. The color image data can be considered as part of the acquired input picture);
display, in overlay on the input picture, information based on information detected by the anomaly detection (Paragraph 53 teaches displaying the anomaly information detected in overlay through a circle or arrow on the image).
However, Im is not relied upon for the below claim language: wherein the acquired starting information comprises: learning execution selection information indicating whether the anomaly detection will perform learning based on the prestored normal picture or perform anomaly detection, and an information selecting what correction to make to the prestored normal picture, or whether to make no correction, when performing the learning; wherein the processor is further configured to execute the program to: perform either the learning or the anomaly detection based on the learning execution selection information included in the starting information; and when performing the learning, if its selected to make correction to the prestored normal picture, perform processing, within a manufacturing site, corresponding to the selected correction on the prestored normal picture before performing the learning.
Nakagawa teaches wherein the acquired starting information comprises: learning execution selection information indicating whether the anomaly detection will perform learning based on the prestored normal picture or perform anomaly detection (Paragraph 17 teaches that the device has an inspection mode and a learning mode. The inspection mode is executing the anomaly detection and the learning mode is performing training. Paragraphs 45 and 53 teach that the user can select the mode on an operation interface. The user selection of the mode teaches the learning execution selection information which is part of the acquired starting information. If the user selects the learning mode, then the anomaly display device will perform training based on training data which are the prestored normal pictures, mentioned in Paragraph 5. If the user selects the inspection mode, then the anomaly display device will execute the anomaly detection), and an information selecting what correction to make to the prestored normal picture, or whether to make no correction, when performing the learning (Paragraph 46-47 teaches when in learning mode, an image processing condition can be selected and performed on the input image. The input image teaches the prestored normal picture and the selection of the image processing condition teaches the information selecting what correction to make; Paragraph 29 teaches the image processing unit can perform corrections like filtering or reducing noise);
wherein the processor is further configured to execute the program to: perform either the learning or the anomaly detection based on the learning execution selection information included in the starting information (Paragraph 17 teaches that the device has an inspection mode and a learning mode. The inspection mode is executing the anomaly detection and the learning mode is performing training. If the user selects the learning mode, then the anomaly display device will perform training based on training data which are the prestored normal pictures, mentioned in Paragraph 5. If the user selects the inspection mode, then the anomaly display device will execute the anomaly detection); and when performing the learning, if its selected to make correction to the prestored normal picture, perform processing, (Paragraph 47 teaches performing image processing or a correction to the prestored normal picture when an image processing condition is selected. The processed image is then output. Paragraphs 48-52 teach operating on this processed or corrected prestored normal picture for learning. Thus, the prestored normal picture is corrected before performing the learning).
Im and Nakagawa are considered analogous to the claimed invention because both are in the same field of anomaly detection. Thus, it would have been obvious to a person holding ordinary skill in the art before the effective filing date to modify the anomaly display device taught by Im with the selection of training or anomaly detection taught by Nakagawa in order to quickly generate large amounts of training data while the model is in learning mode and then perform highly accurate inspections with the trained model (Nakagawa Paragraph 56).
However, Im and Nakagawa are not relied upon for the below claim language: perform processing, within a manufacturing site.
Alasia teaches perform processing, within a manufacturing site (Paragraph 17 “the captured image may be downloaded and processed on-site”. This teaches the image processing can happen within a manufacturing site).
Im and Nakagawa are considered analogous to the claimed invention because both are in the same field of anomaly detection. Alasia is considered analogous to the claimed invention because it is in the same field of processing an object and determining whether it meets certain criteria. Thus, it would have been obvious to a person holding ordinary skill in the art before the effective filing date to modify the anomaly display device taught by Im in view of Nakagawa with processing on-site taught by Alasia in order to allow for a user to carry out inspection on products immediately on-site (Alasia Paragraph 63).
18. Regarding claim 2, Im in view of Nakagawa and Alasia teaches the limitations of claim 1. Im further teaches the anomaly display device wherein: the acquired starting information further includes a path indicating a location at which the input picture is stored (Paragraph 40 teaches the captured image data, which is the input picture, is stored in the second storage. The instructions for the visual inspection device to store the input picture in the second storage can be considered part of the acquired starting information);
and the processor is further configured to execute the program to acquire the input picture stored at the location indicated by the path (Paragraph 52 teaches the optical inspection means acquires the input image from the second storage in order to start the anomaly detection. Thus, the optical inspection means had instructions to acquire the input picture at the location indicated by the path which is the second storage. The optical inspection means includes the input picture acquisition unit).
19. Regarding claim 3, Im in view of Nakagawa and Alasia teaches the limitations of claim 1. Im further teaches the anomaly display device wherein: the acquired starting information includes an image capture starting signal for capturing the image (Paragraph 40 teaches the visual inspection device controls the camera to take images. Thus, this means there is a signal sent to the camera to capture the images. It also has information or instructions to store the image in the second storage);
and the processor is further configured to execute the program to acquire the input picture obtained by the image being captured (Paragraph 52 teaches the optical inspection means acquires the input image from the second storage in order to start the anomaly detection).
20. Regarding claim 8, Im in view of Nakagawa and Alasia teaches the limitations of claim 1. However, Im fails to teach the anomaly display device wherein: the starting information includes training execution selection information indicating whether the anomaly detection is to perform training based on a prescribed normal picture or is to execute the anomaly detection; and the anomaly detection executes either the training or the anomaly detection based on the training execution selection information included in the starting information.
Nakagawa teaches the anomaly display device wherein: the starting information includes training execution selection information indicating whether the anomaly detection is to perform training based on a prescribed normal picture or is to execute the anomaly detection; and the anomaly detection executes either the training or the anomaly detection based on the training execution selection information included in the starting information (Paragraph 17 teaches that the device has an inspection mode and a learning mode. The inspection mode is executing the anomaly detection and the learning mode is performing training. Paragraphs 45 and 53 teach that the user can select the mode on an operation interface. The user selection of the mode can be considered part of the starting information. If the user selects the learning mode, then the anomaly display device will perform training based on training data which can be considered the prescribed normal pictures, mentioned in Paragraph 5. IF the user selects the inspection mode, then the anomaly display device will execute the anomaly detection).
Im and Nakagawa are considered analogous to the claimed invention because both are in the same field of anomaly detection. Alasia is considered analogous to the claimed invention because it is in the same field of processing an object and determining whether it meets certain criteria. Thus, it would have been obvious to a person holding ordinary skill in the art before the effective filing date to modify the anomaly display device taught by Im in view of Alasia with the selection of training or anomaly detection taught by Nakagawa in order to quickly generate large amounts of training data while the model is in learning mode and then perform highly accurate inspections with the trained model (Nakagawa Paragraph 56).
21. Regarding claim 9, Im teaches a non-transitory computer-readable storage medium storing an anomaly display program causing a computer to implement the steps of (Paragraph 31 teaches a control unit that is a general-purpose computer and equipped with a CPU and memories like a hard disk and RAM to execute functions):
acquiring starting information including information for starting an anomaly detection for detecting an anomaly in an image included in an input picture (Paragraphs 35-36 teach a device that runs an anomaly display program. It acquires information about the distance data of the object or substrate in order to start the process of taking photos for anomaly detection. This information can be considered part of the starting information; Paragraph 40 teaches starting the inspection or anomaly detection using information, or starting information, that includes controlling the XY movement to inspect the entire object. Thus, the starting information is acquired to start anomaly detection);
acquiring the input picture (Paragraph 29 teaches a camera that can capture an image of the object; Paragraph 40 teaches capturing images of the object with a camera; Paragraph 52 teaches the optical image inspection means acquires the input image from the second storage in order to start the anomaly detection. The optical image inspection means can be considered the input picture acquisition unit);
executing the anomaly detection, based on the acquired starting information, by comparing the acquired input picture with a prestored normal picture (Paragraph 52 teaches comparing pixels in the color image data to the data in a master image. The master image can be considered a prestored normal picture. The color image data can be considered as part of the acquired input picture);
displaying, in overlay on the input picture, information based on information detected by the anomaly detection (Paragraph 53 teaches displaying the anomaly information detected in overlay through a circle or arrow on the image).
However, Im is not relied upon for the below claim language: wherein the acquired starting information comprises: learning execution selection information indicating whether the anomaly detection will perform learning based on the prestored normal picture or perform anomaly detection, and an information selecting what correction to make to the prestored normal picture, or whether to make no correction, when performing the learning; wherein the processor is further configured to execute the program to: perform either the learning or the anomaly detection based on the learning execution selection information included in the starting information; and when performing the learning, if its selected to make correction to the prestored normal picture, perform processing, within a manufacturing site, corresponding to the selected correction on the prestored normal picture before performing the learning.
Nakagawa teaches wherein the acquired starting information comprises: learning execution selection information indicating whether the anomaly detection will perform learning based on the prestored normal picture or perform anomaly detection (Paragraph 17 teaches that the device has an inspection mode and a learning mode. The inspection mode is executing the anomaly detection and the learning mode is performing training. Paragraphs 45 and 53 teach that the user can select the mode on an operation interface. The user selection of the mode teaches the learning execution selection information which is part of the acquired starting information. If the user selects the learning mode, then the anomaly display device will perform training based on training data which are the prestored normal pictures, mentioned in Paragraph 5. If the user selects the inspection mode, then the anomaly display device will execute the anomaly detection), and an information selecting what correction to make to the prestored normal picture, or whether to make no correction, when performing the learning (Paragraph 46-47 teaches when in learning mode, an image processing condition can be selected and performed on the input image. The input image teaches the prestored normal picture and the selection of the image processing condition teaches the information selecting what correction to make; Paragraph 29 teaches the image processing unit can perform corrections like filtering or reducing noise);
wherein the processor is further configured to execute the program to: perform either the learning or the anomaly detection based on the learning execution selection information included in the starting information (Paragraph 17 teaches that the device has an inspection mode and a learning mode. The inspection mode is executing the anomaly detection and the learning mode is performing training. If the user selects the learning mode, then the anomaly display device will perform training based on training data which are the prestored normal pictures, mentioned in Paragraph 5. If the user selects the inspection mode, then the anomaly display device will execute the anomaly detection); and when performing the learning, if its selected to make correction to the prestored normal picture, perform processing, (Paragraph 47 teaches performing image processing or a correction to the prestored normal picture when an image processing condition is selected. The processed image is then output. Paragraphs 48-52 teach operating on this processed or corrected prestored normal picture for learning. Thus, the prestored normal picture is corrected before performing the learning).
Im and Nakagawa are considered analogous to the claimed invention because both are in the same field of anomaly detection. Thus, it would have been obvious to a person holding ordinary skill in the art before the effective filing date to modify the non-transitory computer-readable storage medium storing an anomaly display program taught by Im with the selection of training or anomaly detection taught by Nakagawa in order to quickly generate large amounts of training data while the model is in learning mode and then perform highly accurate inspections with the trained model (Nakagawa Paragraph 56).
However, Im and Nakagawa are not relied upon for the below claim language: perform processing, within a manufacturing site.
Alasia teaches perform processing, within a manufacturing site (Paragraph 17 “the captured image may be downloaded and processed on-site”. This teaches the image processing can happen within a manufacturing site).
Im and Nakagawa are considered analogous to the claimed invention because both are in the same field of anomaly detection. Alasia is considered analogous to the claimed invention because it is in the same field of processing an object and determining whether it meets certain criteria. Thus, it would have been obvious to a person holding ordinary skill in the art before the effective filing date to modify the non-transitory computer-readable storage medium storing an anomaly display program taught by Im in view of Nakagawa with processing on-site taught by Alasia in order to allow for a user to carry out inspection on products immediately on-site (Alasia Paragraph 63).
22. Regarding claim 10, Im teaches an anomaly display system a processor configured to execute a program to (Paragraph 31 teaches a control unit that is a general-purpose computer and equipped with a CPU that executes functions):
capture an image (Paragraph 29 teaches a camera that can capture an image of the object; Paragraph 40 teaches capturing images of the object with a camera. The camera is the image capture unit);
and wherein the anomaly display system comprise the anomaly display device according to claim 3 (See rejection for claim 3 above),
which executes the anomaly detection on the input picture (Paragraph 52 teaches comparing pixels in the color image data to the data in a master image to detect abnormal pixels or anomalies), and which displays information obtained as a result of the execution (Paragraph 53 teaches displaying the anomaly information detected in overlay through a circle or arrow on the image).
23. Regarding claim 11, claim 11 is the method claim of anomaly display program claim 9 and is accordingly rejected using substantially similar rationale as to that which is set for with respect to claim 9.
24. Claim(s) 4-5 is/are rejected under 35 U.S.C. 103 as being unpatentable over Im (Japanese Patent Application Publication No. 2013-205071 A -- IDS) in view of Nakagawa (WIPO Patent Application Publication No. 2020/071162 A1 -- IDS) and Alasia et al. (U.S. Patent Application Publication No. 2008/0267514 A1), hereinafter referred to as Alasia, as applied to claim 1 above, and further in view of Omura (Japanese Patent Application Publication No. 2018-084443 A -- IDS).
25. Regarding claim 4, Im in view of Nakagawa and Alasia teaches the limitations of claim 1. Im further teaches the anomaly display device, wherein the processor is further configured to execute the program to: (Paragraph 52 teaches comparing pixels in the color image data to the data in a master image. The master image can be considered a prestored normal picture. The color image data can be considered part of the input picture).
However, Im fails to teach correcting the input picture.
Omura teaches correcting the input picture (Paragraph 35 teaches correcting the input image based on a comparison with a reference picture).
Im, Nakagawa, and Omura are considered analogous to the claimed invention because both are in the same field of anomaly detection. Alasia is considered analogous to the claimed invention because it is in the same field of processing an object and determining whether it meets certain criteria. Thus, it would have been obvious to a person holding ordinary skill in the art before the effective filing date to modify the anomaly display device taught by Im in view of Nakagawa and Alasia with the correction unit taught by Omura in order to improve the accuracy in analyzing an object (Omura Paragraph 6).
26. Regarding claim 5, Im in view of Nakagawa, Alasia, and Omura teaches the limitations of claim 4. However, Im fails to teach the anomaly display device, wherein the processor is further configured to execute the program to acquire correction selection information acquisition for selecting a type of correction process to be executed.
Omura teaches the anomaly display device wherein the processor is further configured to execute the program to acquire correction selection information acquisition for selecting a type of correction process to be executed (Paragraph 35 teaches a correction selection information that selects a method based on the comparison result of the input image pixel and reference image. If it is less than a threshold, it will convert the pixel to the reference pixel. Thus, the correction selection information that chooses a type of correction process is acquired through the comparison result).
Im, Nakagawa, and Omura are considered analogous to the claimed invention because both are in the same field of anomaly detection. Alasia is considered analogous to the claimed invention because it is in the same field of processing an object and determining whether it meets certain criteria. Thus, it would have been obvious to a person holding ordinary skill in the art before the effective filing date to modify the anomaly display device taught by Im in view of Nakagawa and Alasia with the correction unit taught by Omura in order to improve the accuracy in analyzing an object (Omura Paragraph 6).
27. Claim(s) 6 is/are rejected under 35 U.S.C. 103 as being unpatentable over Im (Japanese Patent Application Publication No. 2013-205071 A -- IDS) in view of Nakagawa (WIPO Patent Application Publication No. 2020/071162 A1 -- IDS) and Alasia et al. (U.S. Patent Application Publication No. 2008/0267514 A1), hereinafter referred to as Alasia, as applied to claim 1 above, and further in view of Wang (Chinese Patent Application Publication No. 112418353 A -- IDS).
Regarding claim 6, Im in view of Nakagawa and Alasia teaches the limitations of claim 1. However, Im fails to teach the anomaly display device wherein the anomaly detection is pretrained by a prescribed normal picture.
Wang teaches the anomaly display device wherein the anomaly detection is pretrained by a prescribed normal picture (Paragraph 29 teaches a training image set consists of images that pass the inspection, thus having no anomaly).
Im, Nakagawa, and Wang are considered analogous to the claimed invention because both are in the same field of anomaly detection. Alasia is considered analogous to the claimed invention because it is in the same field of processing an object and determining whether it meets certain criteria. Thus, it would have been obvious to a person holding ordinary skill in the art before the effective filing date to modify the anomaly display device taught by Im in view of Nakagawa and Alasia with the training taught by Wang in order to train the detection unit to know what are positive samples and what are abnormal features (Wang Paragraph 10).
28. Claim(s) 7 is/are rejected under 35 U.S.C. 103 as being unpatentable over Im (Japanese Patent Application Publication No. 2013-205071 A -- IDS) in view of Nakagawa (WIPO Patent Application Publication No. 2020/071162 A1 -- IDS) and Alasia et al. (U.S. Patent Application Publication No. 2008/0267514 A1), hereinafter referred to as Alasia, as applied to claim 1 above, and further in view of Saito et al. (Japanese Patent Application Publication No. 2007-132757 A -- IDS), hereinafter referred to as Saito.
Regarding claim 7, Im, Nakagawa and Alasia teaches the limitations of claim 1. However, Im fails to teach the anomaly display device wherein: the information based on the prestored normal picture includes information on a mean value vector and variance of the prestored normal picture; and the processor is further configured to execute the program to perform anomaly detection corresponding to multiple split regions, which are regions into which the input picture has been split; and display, in overlay on the input picture, the information detected, so as to be associated with the multiple split regions.
Saito teaches the anomaly display device wherein: the information based on the prestored normal picture includes information on a mean value vector and variance of the prestored normal picture (Paragraph 78 teaches calculating an average vector, or mean value vector, and a covariance matrix, or variance, from the images of non-defective products. Thes values are set as feature reference values. The images of non-defective products are the prestored normal pictures. Thus, the feature reference values which have information on the mean value vector and variance are based on a prestored normal picture);
and the processor is further configured to execute the program to perform anomaly detection corresponding to multiple split regions, which are regions into which the input picture has been split (Paragraph 11 teaches an area division step which divides the picture into multiple split regions);
and display, in overlay on the input picture, the information detected, so as to be associated with the multiple split regions (Paragraph 109-111 teach splitting the image into multiple regions and then if a defect is found during that process, it will display the location on the monitor. Displaying the location of the defect associates it with at least one of the split regions since each split region has its own location).
Im, Nakagawa, and Saito are considered analogous to the claimed invention because both are in the same field of anomaly detection. Alasia is considered analogous to the claimed invention because it is in the same field of processing an object and determining whether it meets certain criteria. Thus, it would have been obvious to a person holding ordinary skill in the art before the effective filing date to modify the anomaly display device taught by Im in view of Nakagawa and Alasia with the prestored normal picture information and splitting the input image into regions as taught by Saito in order to identify defects that are not just local but also global (Saito Paragraphs 9-10).
Conclusion
29. Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). 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.
30. Any inquiry concerning this communication or earlier communications from the examiner should be directed to CHRISTINE Y AHN whose telephone number is (571)272-0672. The examiner can normally be reached M-F 9-5pm.
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, Alicia Harrington can be reached at (571)272-2330. 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.
/CHRISTINE YERA AHN/Examiner, Art Unit 2615
/ALICIA M HARRINGTON/Supervisory Patent Examiner, Art Unit 2615