Office Action Predictor
Last updated: April 15, 2026
Application No. 18/757,281

IMAGE PROCESSING APPARATUS, IMAGE PROCESSING METHOD, AND NON-TRANSITORY COMPUTER-READABLE STORAGE MEDIUM

Non-Final OA §103
Filed
Jun 27, 2024
Examiner
SMITH, MAURICE C
Art Unit
2877
Tech Center
2800 — Semiconductors & Electrical Systems
Assignee
Canon Kabushiki Kaisha
OA Round
1 (Non-Final)
84%
Grant Probability
Favorable
1-2
OA Rounds
2y 1m
To Grant
82%
With Interview

Examiner Intelligence

Grants 84% — above average
84%
Career Allow Rate
594 granted / 704 resolved
+16.4% vs TC avg
Minimal -2% lift
Without
With
+-2.3%
Interview Lift
resolved cases with interview
Fast prosecutor
2y 1m
Avg Prosecution
33 currently pending
Career history
737
Total Applications
across all art units

Statute-Specific Performance

§101
3.7%
-36.3% vs TC avg
§103
47.3%
+7.3% vs TC avg
§102
17.1%
-22.9% vs TC avg
§112
30.2%
-9.8% vs TC avg
Black line = Tech Center average estimate • Based on career data from 704 resolved cases

Office Action

§103
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 . 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. Claim(s) 1, 2, 3, 11, & 15 is/are rejected under 35 U.S.C. 103 as being unpatentable over paper of Xuan Zhang, “Stud Pose Detection Based on Photometric Stereo and Lightweight YOLOv4”, 27 December 2021 hereafter Zhang in view of Ramani US 20210134065 in further view of paper of Nicholas J. Durr, “System for Clinical Photometric Stereo Endoscopy”, 2014 hereafter Durr in further view of paper of Frank Verbiest, “Photometric Stereo with Coherent Outlier Handling and Confidence Estimation”, 2008 hereafter Verbiest. With respect to claim 1, Zhang teaches an image processing apparatus comprising: execution of the instructions causes the one or more processors (fig 1, computer) to: obtain a normal map (fig 1, normal map) indicating a spatial distribution of “surface normal” (pg. 34, col 1, ¶ 3) on a surface of an object “reflection of the stud” (pg. 33, col 2, ¶ 2, lines 6-7); obtain a direction vector (fig 1, vector map) of a light source according to a variation in orientation of the object; and perform processing for detecting a linear feature (fig 1, stud) on the surface based on the normal map and the direction vector “normal maps of studs are obtained…vector map” (pg. 35, col 1, ¶ 3, lines 4-7). PNG media_image1.png 168 248 media_image1.png Greyscale Zhang does not teach one or more processors coupled to the one or more memories. Ramani, in the same field of endeavor as Zhang of stereo imaging (0029), teaches instructions stored on the memory for execution by the processor, the programmed instructions being configured to cause the processor to perform a task of imaging an object (claim 19). At the time prior to the effective filing date of the invention it would have been obvious to one of ordinary skill in the art to combine memory with Zhang’s processor to automatically cause the processor to perform steps of imaging an object since it is a known technique for the improvement of imaging with a reasonable expectation of success. The combination does not specifically teach indicating a spatial distribution of normal. Durr, in the same field of endeavor as Zhang of Photometric normal maps, teaches a normal map is made up of light of several vectors, wherein red, blue, and green lights represent normal vectors relative to the surface of an object (fig 3, captions). Examiner notes one of ordinary skill would recognize red, blue, and green colors on a normal map would represent the spatial distribution of normal vectors on the surface of an object. At the time prior to the effective filing date of the invention it would have been obvious to one of ordinary skill to indicate a spatial distribution of normal light via Zhang’s normal map to accurately reconstruct the topology of an object. The combination does not teach a virtual light source. Verbiest, in the same field of endeavor as Zhang of Photometric normal maps (pg. 3, ¶ 3, lines 1-3 Verbiest), teaches capturing images of normal map (fig 5) from a virtual light source (pg. 5, ¶ 3, lines 1-5) (fig 5, caption). At the time prior to the effective filing of the invention it would have been obvious to one of ordinary skill to combine a virtual light with the combination’s processor as a known technique for producing a normal map. PNG media_image2.png 224 146 media_image2.png Greyscale With respect to claim 2 according to claim 1, the image processing apparatus wherein the processing for detecting a linear feature on the surface includes processing for detecting a linear protrusion/recess “automatically labelling the studs” (pg. 33, col 1, ¶ 2, lines 8-10 Durr) on the surface. With respect to claim 3 according to claim 1, the image processing apparatus wherein execution of the instructions further causes the one or more processors “microcontroller program” to obtain the normal map based on a plurality of captured images “eight stud images” obtained by imaging the object with each of a plurality of light sources sequentially lit “LEDs are lit in the clockwise” (pg. 34, col 2, ¶ 4, lines 2-6). With respect to claim 11 according to claim 1, the image processing apparatus wherein the variation in orientation is an inclination of the object (fig 1, Zhang). With respect to claim 15, Zhang teaches a computer configured to: obtain a normal map (fig 1, normal map) indicating a spatial distribution of “surface normal” (pg. 34, col 1, ¶ 3) on a surface of an object “reflection of the stud” (pg. 33, col 2, ¶ 2, lines 6-7); obtain a direction vector (fig 1, vector map) of a light source according to a variation in orientation of the object; and perform processing for detecting a linear feature (fig 1, stud) on the surface based on the normal map and the direction vector “normal maps of studs are obtained…vector map” (pg. 35, col 1, ¶ 3, lines 4-7). Zhang does not teach storing computer executable instructions that, when executed, cause a computer: Ramani, in the same field of endeavor as Zhang of stereo imaging (0029), teaches instructions stored on the memory for execution by the processor, the programmed instructions being configured to cause the processor to perform a task of imaging an object (claim 19). At the time prior to the effective filing date of the invention it would have been obvious to one of ordinary skill in the art to combine memory with Zhang’s processor to automatically cause the processor to perform steps of imaging an object since it is a known technique for the improvement of imaging with a reasonable expectation of success. The combination does not specifically teach indicating a spatial distribution of normal. Durr, in the same field of endeavor as Zhang of Photometric normal maps, teaches a normal map is made up of light of several vectors, wherein red, blue, and green lights represent normal vectors relative to the surface of an object (fig 3, captions). Examiner notes one of ordinary skill would recognize red, blue, and green colors on a normal map would represent the spatial distribution of normal vectors on the surface of an object. At the time prior to the effective filing date of the invention it would have been obvious to one of ordinary skill to indicate a spatial distribution of normal light via Zhang’s normal map to accurately reconstruct the topology of an object. The combination does not teach a virtual light source. Verbiest, in the same field of endeavor as Zhang of Photometric normal maps (pg. 3, ¶ 3, lines 1-3 Verbiest), teaches capturing images of normal map (fig 5) from a virtual light source (pg. 5, ¶ 3, lines 1-5) (fig 5, caption). At the time prior to the effective filing of the invention it would have been obvious to one of ordinary skill to combine a virtual light with the combination’s processor as a known technique for producing a normal map. PNG media_image3.png 265 173 media_image3.png Greyscale Claim(s) 14 is/are rejected under 35 U.S.C. 103 as being unpatentable over Xuan Zhang, “Stud Pose Detection Based on Photometric Stereo and Lightweight YOLOv4”, 27 December 2021 hereafter Zhang in view of paper of Nicholas J. Durr, “System for Clinical Photometric Stereo Endoscopy”, 2014 hereafter Durr in further view of paper of Frank Verbiest, “Photometric Stereo with Coherent Outlier Handling and Confidence Estimation”, 2008 hereafter Verbiest. With respect to claim 14, Zhang teaches an image processing method comprising: obtaining a normal map (fig 1, normal map)indicating a spatial distribution on a surface “surface normal” (pg. 34, col 1, ¶ 3) of an object; obtaining a direction vector (fig 1, vector map) of a light source according to a variation in orientation of the object; and performing processing for detecting a linear feature (fig 1, stud) on the surface based on the normal map and the direction vector “normal maps of studs are obtained…vector map” (pg. 35, col 1, ¶ 3, lines 4-7). PNG media_image1.png 168 248 media_image1.png Greyscale Zhang does not specifically teach indicating a spatial distribution of normal. Durr, in the same field of endeavor as Zhang of Photometric normal maps, teaches a normal map is made up of light of several vectors, wherein red, blue, and green lights represent normal vectors relative to the surface of an object (fig 3, captions). Examiner notes one of ordinary skill would recognize red, blue, and green colors on a normal map would represent the spatial distribution of normal vectors on the surface of an object. At the time prior to the effective filing date of the invention it would have been obvious to one of ordinary skill to indicate a spatial distribution of normal light via Zhang’s normal map to accurately reconstruct the topology of an object. The combination does not teach a virtual light source. Verbiest, in the same field of endeavor as Zhang of Photometric normal maps (pg. 3, ¶ 3, lines 1-3 Verbiest), teaches capturing images of normal map (fig 5) from a virtual light source (pg. 5, ¶ 3, lines 1-5) (fig 5, caption). At the time prior to the effective filing of the invention it would have been obvious to one of ordinary skill to combine a virtual light with the combination’s processor as a known technique for producing a normal map. PNG media_image4.png 265 173 media_image4.png Greyscale Allowable Subject Matter Claims 4-10, 12, & 13 are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten to include all of the limitations of the base claim and any intervening claims or to include the limitation(s) and any intervening claims into the base claim. The following is a statement of reasons for the indication of allowable subject matter: As to claim 4, the prior art of record, taken alone or in combination, fails to disclose or render obvious “obtain a luminance distribution on the surface based on the normal map and the direction vector; and perform the detection processing based on the luminance distribution”, in combination with the rest of the limitations of claim 4. As to claim 7, the prior art of record, taken alone or in combination, fails to disclose or render obvious “in a case where the variation in orientation is greater than or equal to a threshold, change the direction vector of the virtual light source according to the variation in orientation”, in combination with the rest of the limitations of claim 7. As to claim 8, the prior art of record, taken alone or in combination, fails to disclose or render obvious “in a case where the variation in orientation is less than a threshold and an angle formed by a direction vector of a first virtual light source and a direction vector of a second virtual light source adjacent to the direction vector of the first virtual light source is less than a threshold, obtain the direction vector”, in combination with the rest of the limitations of claim 8. As to claim 9, the prior art of record, taken alone or in combination, fails to disclose or render obvious “in a case where the variation in orientation is less than a threshold and an angle formed by a direction vector of a first virtual light source and a direction vector of a second virtual light source adjacent to the direction vector of the first virtual light source is greater than or equal to a threshold, change the direction”, in combination with the rest of the limitations of claim 9. As to claim 10, the prior art of record, taken alone or in combination, fails to disclose or render obvious “change a vector of an irradiation direction set in advance as an irradiation direction of light to be irradiated on the surface for detection of a linear protrusion/recess on the surface, according to the variation in orientation”, in combination with the rest of the limitations of claim 10. As to claim 12, the prior art of record, taken alone or in combination, fails to disclose or render obvious “the variation in orientation is an angle of rotation of the object on one plane”, in combination with the rest of the limitations of claim 12. As to claim 13, the prior art of record, taken alone or in combination, fails to disclose or render obvious “the variation in orientation includes an angle of rotation of the object on a first plane and an angle of rotation of the object on a second plane”, in combination with the rest of the limitations of claim 13. Conclusion Any inquiry concerning this communication or earlier communications from the examiner should be directed to MAURICE C SMITH whose telephone number is (571)272-2526. 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, Kara Geisel can be reached at (571) 272-2416. 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. /MAURICE C SMITH/Examiner, Art Unit 2877
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Prosecution Timeline

Jun 27, 2024
Application Filed
Dec 01, 2025
Non-Final Rejection — §103
Mar 31, 2026
Response Filed

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Study what changed to get past this examiner. Based on 5 most recent grants.

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Prosecution Projections

1-2
Expected OA Rounds
84%
Grant Probability
82%
With Interview (-2.3%)
2y 1m
Median Time to Grant
Low
PTA Risk
Based on 704 resolved cases by this examiner. Grant probability derived from career allow rate.

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