Prosecution Insights
Last updated: April 19, 2026
Application No. 18/579,930

IMAGE PROCESSING DEVICE, IMAGE PROCESSING METHOD, AND RECORDING MEDIUM

Non-Final OA §103
Filed
Jan 17, 2024
Examiner
ALAVI, AMIR
Art Unit
2668
Tech Center
2600 — Communications
Assignee
NEC Corporation
OA Round
1 (Non-Final)
94%
Grant Probability
Favorable
1-2
OA Rounds
2y 5m
To Grant
97%
With Interview

Examiner Intelligence

Grants 94% — above average
94%
Career Allow Rate
1083 granted / 1156 resolved
+31.7% vs TC avg
Minimal +4% lift
Without
With
+3.6%
Interview Lift
resolved cases with interview
Typical timeline
2y 5m
Avg Prosecution
23 currently pending
Career history
1179
Total Applications
across all art units

Statute-Specific Performance

§101
23.0%
-17.0% vs TC avg
§103
20.2%
-19.8% vs TC avg
§102
19.5%
-20.5% vs TC avg
§112
12.9%
-27.1% vs TC avg
Black line = Tech Center average estimate • Based on career data from 1156 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 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 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. 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 set forth in Graham v. John Deere Co., 383 U.S. 1, 148 USPQ 459 (1966), that are applied 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 1-20 are rejected under 35 U.S.C. 103 as being unpatentable over Chen (USPAP 2010/0070,527), in view of Jung et al. (USPAP 2009/0123,021), hereinafter, “Jung”. Regarding claim 1 Chen teaches, at least one memory storing instructions; and at least one processor configured to access the at least one memory (Please note, paragraph 0013. As indicated storing a plurality of items in a raw data storage, the items comprising images and/or videos, processing the items in a processor.) and execute the instructions to: set, as a candidate region, a region in which an object to be annotated is likely to be present in an annotation target image (Please note, paragraph 0013. As indicated to generate and/or segment annotated information from the items and to extract object, activity and/or metadata information from the items in the first data storage.); generate, as annotation data, data in which the annotation target image, a reference image captured when a region including the candidate region is different from the annotation target image, and the standard image are associated with each other (Please note, paragraph 0010. As indicated providing at least data types of object and activity where the object is a data type representing a thing or a being with visual shape in an image or video frame and the activity is a data type representing an action or an event visually shown in an image or video or video frame such as an explosion, person movement, vehicle movement and so on, providing a function of identify( ) by given a first item to find a list of items that are similar to the first item or to identify the identity of the first item; and the item can be a video or a video frame, or an image or a set of images, or a template extracted from a video or image or images, or an object, or an activity, or an annotated data; and the annotated data is a characteristic or summary representation of its original video or images; and providing a function of compose( ) which creates a complex object from a plurality of existing objects with or without a defined manor, or creates a complex activity from a plurality of existing objects and/or activities; and the manor is an orientation or an order in which objects are located in physically or logically.); and output the generated annotation data. (Please note, figure 1, block 121). Chen does not expressly teach, extract a standard image that is an image in which an object identical to the object to be annotated is imaged from an annotated image. Jung teaches, extract a standard image that is an image in which an object identical to the object to be annotated is imaged from an annotated image (Please note, paragraph 0043. As indicated referring to FIG. 3, an example is described in which a word "wedding ceremony", as the user's annotation, is inputted in a particular photo of photos included in a segment #1, and a word "wedding reception", as the user's annotation, is inputted in a particular photo of photos included in a segment #2. The user's annotation analyzer 151 may analyze an identical event and up-down relationship through the user's annotation, "wedding ceremony" and "wedding reception".). Chen & Jung are combinable because they are from the same field of endeavor. At the time before the effective filing date, it would have been obvious to a person of ordinary skill in the art to utilize this extract a standard image that is an image in which an object identical to the object to be annotated is imaged from an annotated image of Jung in Chen’s invention. The suggestion/motivation for doing so would have been as indicated on paragraph 0043, “as a result of the analyzing. Specifically, the user's annotation extraction unit 150 may analyze the identical event and up-down relationship via the user's annotation analyzer 151, and may extract the shared index based on the result of the analyzing via the shared index extraction unit 152.”. Therefore, it would have been obvious to combine Jung with Chen to obtain the invention as specified in claim 1. Regarding claim 2 Chen teaches, receive, as annotation information, input of information related to annotation of the object to be annotated on the annotation target image; and in a storage as annotation completion data, the annotation target image and the annotation information in association with each other. (Please note, paragraph 0034. As indicated referring to FIG. 1, when new query language statements get input 101 into the database of objects and activities, a new query language parser 103 will parse the statements into token streams, which are then handed over to a (optional) query Planner 105 for evaluating various possible query paths and choose an optimal one for execution, and trigger internal handling functions in Execution Engine 113 to execute the actual query, the Execution Engine 113 will search through primary storage 115 with indexation (following indexed search path set by Indexation Engine 109) or without indexation (a default maybe-brutal searching path will be followed) to fulfill the query tasks and then generate results 121 and return to user, including pulling out relevant annotated data from secondary data storage 117 and raw data from raw data storage 119 to represent to user as part of query output 121.). Regarding claim 3 Jung teaches, store, in the storage, an image included in the annotation completion data and information about an imaging position of the image in association with each other (Please note, paragraph 0040. As indicated the database 140 may include an annotation database 141, a photo database 142, and an index database 142, for example. The database 140 may store and maintain a user's annotation, the photo, and the index. Specifically, the annotation database 141 may store and maintain the user's annotation inputted via the user's annotation input unit 111. The photo database 142 may store and maintain the photo encoded by the photo encoding unit 130, and the index database 143 may store and maintain the index generated by the indexing unit 180, for example.); and compare an image obtained by imaging a location identical to the candidate region among images stored in the storage means with an image of the candidate region of the annotation target image to extract the standard image. (Please note, paragraph 0055. As indicated in order to prevent a repeated extraction with respect to a portion of the photos which is not changed compared to a previous photo when analyzing the plurality of photos, the individual situation inference unit 170 may deduce the date and time, the location, the person, the event, the object, a behavior or a pose, and the category with respect to only a changed portion, after the situation change detection unit 160 determines an unchanged portion, for example. As an example, when an individual situation is a date and time, the individual situation inference unit 170 may analyze the date and time information as photo information included in the plurality of photos, and may automatically deduce a user's annotation associated with a source time of the plurality of photos.). Regarding claim 4 Jung teaches, compare each image of the annotation completion data stored in the storage with the annotation target image to extract the standard image when an image obtained by imaging a location identical to the candidate region is not stored in the storage. (Please note, paragraph 0055. As indicated the individual situation inference unit 170 may analyze the plurality of photos stored in the photo database 142 and may deduce any one or more of a date and time (when), a location (where), a person (who), an event (what occasion), an object (with which thing), a behavior or pose (which action), and a category (which category). Also, in an embodiment, in order to prevent a repeated extraction with respect to a portion of the photos which is not changed compared to a previous photo when analyzing the plurality of photos, the individual situation inference unit 170 may deduce the date and time, the location, the person, the event, the object, a behavior or a pose, and the category with respect to only a changed portion, after the situation change detection unit 160 determines an unchanged portion, for example. As an example, when an individual situation is a date and time, the individual situation inference unit 170 may analyze the date and time information as photo information included in the plurality of photos, and may automatically deduce a user's annotation associated with a source time of the plurality of photos. The source time may refer to a time when the photo is taken, for example. As another example, when the individual situation is a location, the individual situation inference unit 170 may analyze location information, for example, GPS information, as the photo information included in the plurality of photos, and may automatically deduce the user's annotation associated with a source location of the plurality of photos.). Regarding claim 5 Chen teaches, output, as the standard image, an image in which a determination result at a time of performing annotation is correct and an image in which the determination result is incorrect. (Please note, paragraph 0034. As indicated referring to FIG. 1, when new query language statements get input 101 into the database of objects and activities, a new query language parser 103 will parse the statements into token streams, which are then handed over to a (optional) query Planner 105 for evaluating various possible query paths and choose an optimal one for execution, and trigger internal handling functions in Execution Engine 113 to execute the actual query, the Execution Engine 113 will search through primary storage 115 with indexation (following indexed search path set by Indexation Engine 109) or without indexation (a default maybe-brutal searching path will be followed) to fulfill the query tasks and then generate results 121 and return to user, including pulling out relevant annotated data from secondary data storage 117 and raw data from raw data storage 119 to represent to user as part of query output 121.). Regarding claim 6 Chen teaches, extract, as a related image, an image of a region related to the candidate region from the reference image (Please note, paragraph 0013. As indicated to generate and/or segment annotated information from the items and to extract object, activity and/or metadata information from the items in the first data storage.); and output as the annotation data, data in which an image of the candidate region, the related image, and the standard image are associated with each other. (Please note, paragraph 0010. As indicated providing at least data types of object and activity where the object is a data type representing a thing or a being with visual shape in an image or video frame and the activity is a data type representing an action or an event visually shown in an image or video or video frame such as an explosion, person movement, vehicle movement and so on, providing a function of identify( ) by given a first item to find a list of items that are similar to the first item or to identify the identity of the first item; and the item can be a video or a video frame, or an image or a set of images, or a template extracted from a video or image or images, or an object, or an activity, or an annotated data; and the annotated data is a characteristic or summary representation of its original video or images; and providing a function of compose( ) which creates a complex object from a plurality of existing objects with or without a defined manor, or creates a complex activity from a plurality of existing objects and/or activities; and the manor is an orientation or an order in which objects are located in physically or logically.). Regarding claim 7 Jung teaches, set a plurality of the candidate regions by sliding a position of the candidate region on the annotation target image. (Please note, figure 2). Regarding claim 8 Jung teaches, set the candidate region at a position where the object to be annotated is likely to be present based on map information and a type of the object to be annotated. (Please note, figure 4). Regarding claims 9, 11-17, analysis similar to those presented for claims 1-8, are applicable. Regarding claims 10, 18-20, analysis similar to those presented for claims 1-8, are applicable. Examiner’s Note The examiner cites particular figures, paragraphs, columns and line numbers in the references as applied to the claims for the convenience of the applicant. Although the specified citations are representative of the teachings in the art and are applied to the specific limitations within the individual claims, other passages and figures may apply as well. It is respectfully requested that, in preparing responses, the applicant fully consider the references in their entirety as potentially teaching all or part of the claimed invention, as well as the context of the passage as taught by the prior art or disclosed by the examiner. Any inquiry concerning this communication or earlier communications from the examiner should be directed to AMIR ALAVI whose telephone number is (571)272-7386. The examiner can normally be reached on M-F from 8:00-4:30. 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, Vu Le can be reached at (571)272-7332. 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. /AMIR ALAVI/Primary Examiner, Art Unit 2668 Wednesday, January 14, 2026
Read full office action

Prosecution Timeline

Jan 17, 2024
Application Filed
Jan 14, 2026
Non-Final Rejection — §103 (current)

Precedent Cases

Applications granted by this same examiner with similar technology

Patent 12597232
SYSTEM FOR LEARNING NEW VISUAL INSPECTION TASKS USING A FEW-SHOT META-LEARNING METHOD
2y 5m to grant Granted Apr 07, 2026
Patent 12573189
PROCESSING METHOD AND PROCESSING DEVICE USING SAME
2y 5m to grant Granted Mar 10, 2026
Patent 12567238
GENERATING A DATA STRUCTURE FOR SPECIFYING VISUAL DATA SETS
2y 5m to grant Granted Mar 03, 2026
Patent 12561950
AI System and Method for Automatic Analog Gauge Reading
2y 5m to grant Granted Feb 24, 2026
Patent 12561774
SYSTEM AND METHOD FOR REAL-TIME TONE-MAPPING
2y 5m to grant Granted Feb 24, 2026
Study what changed to get past this examiner. Based on 5 most recent grants.

AI Strategy Recommendation

Get an AI-powered prosecution strategy using examiner precedents, rejection analysis, and claim mapping.
Powered by AI — typically takes 5-10 seconds

Prosecution Projections

1-2
Expected OA Rounds
94%
Grant Probability
97%
With Interview (+3.6%)
2y 5m
Median Time to Grant
Low
PTA Risk
Based on 1156 resolved cases by this examiner. Grant probability derived from career allow rate.

Sign in with your work email

Enter your email to receive a magic link. No password needed.

Personal email addresses (Gmail, Yahoo, etc.) are not accepted.

Free tier: 3 strategy analyses per month