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 .
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 .
Response to Amendment
1. This office action is in response to communications filed 5/12/2026 Claims 1, 10, 17, and 18 are amended. Claim 2 is original. Claims 3, 4, 5, 6, 9, 10, 11, 12, 13, 15 and 16 are previously presented. Claims 7 and 8 are canceled. Claims 19 and 20 are new.
Response to Arguments
Applicant's arguments filed 5/12/2026 have been fully considered but they are not persuasive.
Applicant argues that “Wang fails to teach or suggest adjusting images acquired by using the plurality of comers to that the images conform to a predetermined standard.” This argument mischaracterizes the bases of the rejection. The Office Action did not rely on Wang as explicitly disclosing this limitation; rather, the rejection expressly stated that “Wang does not explicitly disclose that these adjustments of the images are ‘in conformity with a particular standard,”’ and instead relied on the well-known state of the art to support a conclusion of obviousness under 35 U.S.C 103.
Applicant’s response address the rejection as though it were made under 35 U.S.C. 102 (anticipation), attacking only whether Wang itself “teaches or suggests” the limitation in isolation, without addressing the Office’s actual rationale namely, that a person of ordinary skill in the art, prior to the effective filing date, would have found it obvious to implement Wang’s disclosed compression and video analytics processing using algorithms conforming to a predetermined/ known standard, in order to yield predictable results and ensure faithful, consistent reproduction of content across networked devices. Applicant has not specifically traversed this well-known in the art assertion, nor provided argument or evidence that such conformity-to-standard processing across multiple networked image capture devices was not, in fact well-known.
Moreover, to the extent Applicant’s arguments can be construed as requesting evidentiary support for the well-known nature of this practice, Examiner further relies on the multi-camera image correction art of record. For example, U.S. Patent Application 2018/0249088 Chang, directed to a method for correcting images from a multi-camera system ([0046]-[0047), discloses that where multiple cameras capture images of the same subject, camera settings and outputs are calibrated so that “ideal images will have the same location, angle, and size” see [0059], and so that images from each camera are adjusted using calibration parameters to correct geometric error such that “the resulting image becomes the ideal image” see [0066],- i.e., adjusting images acquired using each of a plurality of cameras so that the images conform to a predetermined/ideal standard. This confirms that adjusting images from a plurality of cameras to conform to a common, predetermined standard was a well-known technique in the art of multi-camera image processing systems, of the same general character as the surveillance/imaging system disclosed by Wang. It would have been obvious to one of ordinary skill in the art to apply this known technique to standard-conformity adjustment to the first-tier image processing disclosed by Wang, in order to yield predictable, consistent image output across Wang’s plurality of cameras, with a reasonable expectation of success.
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.
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.
1. Claim(s) 1, 9, 10, 14, 15, 16, 17 and 18 are rejected under 35 U.S.C. 103 as being unpatentable over U.S. Patent 10,769,913 Wang et al. (hereinafter Wang) in view of U.S. Patent Application 2018/0249088, Chang.
2. Regarding Claim 1, Wang discloses An image processing apparatus (Title: “Cloud-based Video Surveillance Management system”) comprising:
at least one memory storing instructions (Fig. 8: working memory 235, see Col. 15 lines 29-44); and
at least one processor (Fig. 8: processor(s)) configured to execute the instructions to (See Col. 16 lines 9-12, “processor 210 executing one or more sequences of one or more instructions”):
receive an image acquired by using each of a plurality of cameras (Fig. 1: 12, 14, 16 camera(s), Col. 4 lines 45-48, “Each camera is equipped with an imaging module, that generates images from received light”);
perform first image processing on the received image (Col. 9 Lines 8-11, “The first tier 40 of the system includes edge devices such as routers 20, intelligent encoders and intelligent cameras 42 with embedded video analytics algorithms” Each camera captures video and performs some on-board processing (e.g., compression or basic analytics) These correspond to “first severs.” Col. 9 lines 34-37, “a video analytics algorithm is utilized as a scene analyzer to detect and track objects in the scene and generate metadata to describe the objects and their events”); and
transmit the image on which the first image processing has been performed to a server configured to perform second image processing on the image on which the first image processing has been performed (Fig. 2; Col. 9 lines 12-17, “The first tier 40 of the system connects to the second tier 50 of the system through one or more LANs 32. The second tier 50 of the system is at the gateway of the surveillance system and includes one or more gateway devices 52.” Col. 9 lines 46-49, “The gateway 52 is a storage and processing device in the local network which stores video and metadata content. The gateway can be wholly or in part implemented as a network video recorder or an independent server.”),
wherein the first image processing includes processing comprising adjusting images acquired by using the plurality of cameras so that the images conform to a predetermined standard. Wang adjusts acquired images in two ways: compression of the images and the generation of image metadata.
Wang does not explicitly disclose that these adjustments of the images are 'in conformity with a particular standard', but this is not considered to be a patentable distinction. It was notoriously well-known in the art prior to the effective filing date of the invention to use standard algorithms across devices in a network to ensure conformity to a known standard. Video compression standards were well-stablished in the art as a means to ensure the faithful reproduction of content. Further, the use of a standard video analytics algorithm across all devices would yield predictable results in terms of metadata generation. Accordingly, it would have been obvious to one of ordinary skill in the art prior to the effective filing date of the invention to implement Wang with compression and video analytics algorithms that conform to a particular standard for the stated advantages.
Chang, directed to a method for correcting images from a multi-camera system ([0046]-[0047), discloses that where multiple cameras capture images of the same subject, camera settings and outputs are calibrated so that “ideal images will have the same location, angle, and size” see [0059], and so that images from each camera are adjusted using calibration parameters to correct geometric error such that “the resulting image becomes the ideal image” see [0066],- i.e., adjusting images acquired using each of a plurality of cameras so that the images conform to a predetermined/ideal standard. This confirms that adjusting images from a plurality of cameras to conform to a common, predetermined standard was a well-known technique in the art of multi-camera image processing systems, of the same general character as the surveillance/imaging system disclosed by Wang. It would have been obvious to one of ordinary skill in the art to apply this known technique to standard-conformity adjustment to the first-tier image processing disclosed by Wang, in order to yield predictable, consistent image output across Wang’s plurality of cameras, with a reasonable expectation of success.
3. Regarding Claim 9, Wang discloses An image processing system (Title: “Cloud-based Video Surveillance Management system”) comprising:
one or more first servers each comprising the image processing apparatus (Col. 9 Lines 8-11, “The first tier 40 of the system includes edge devices such as routers 20, intelligent encoders and intelligent cameras 42 with embedded video analytics algorithms” Each camera captures video and performs some on-board processing (e.g., compression or basic analytics) These correspond to “first severs.”) according to claim 1; and
a second server configured to receive an image on which the first image processing has been performed from the first servers, and to perform second image processing on the received image (Fig. 2; Col. 9 lines 12-17, “The first tier 40 of the system connects to the second tier 50 of the system through one or more LANs 32. The second tier 50 of the system is at the gateway of the surveillance system and includes one or more gateway devices 52.” Col. 9 lines 46-49, “The gateway 52 is a storage and processing device in the local network which stores video and metadata content. The gateway can be wholly or in part implemented as a network video recorder or an independent server.”).
4. Regarding Claim 10, Wang discloses The image processing system according to claim 9, wherein the first image processing includes image correction processing (Col. 4 lines 50-53, “compresses the image data using a visual compression algorithm and sends the compressed data over a local connection.” Cameras/encoders perform local pre-processing such as compression to correct or prepare the image date before transmission to the gateway), and
the second image processing includes image analysis processing (Col. 10 lines 4-6 and Col. 6 lines 12-16, “For instance, algorithms such as face detection/recognition and license plate recognition can be executed at the gateway 52 to extract information based on motion detection results from the associated cameras 42”)
5. Regarding Claim 14, Wang discloses The image processing system according to claim 9, wherein
a plurality of the first servers are provided (Fig. 2: describes a plurality of cameras/ encoders at the first tier, each performing local pre-processing (compression, analytics) on its own image stream. Each of those devices functions as a “first server”), and
the second server receives an image on which the first image processing has been performed from the plurality of first servers (Fig. 2: discloses a gateway 52 (second server) that receives image data and metadata from multiple first-tier devices and performs further processing before sending results to the cloud).
6. Regarding Claim 15, Wang discloses The image processing system according to claim 9, wherein
a plurality of sets of the plurality of first servers (Fig. 2: describes a plurality of cameras/ encoders at the first tier, each performing local pre-processing (compression, analytics) on its own image stream. Each of those devices functions as a “first server”)and a plurality of the second servers are provided (Fig. 2: discloses a gateway 52 (second server) that receives image data and metadata from multiple first-tier devices and performs further processing before sending results to the cloud), and
a third server configured to receive a result of the second image processing from the second servers in the plurality of sets is further provided (Col. 9 lines “As a result of metadata filtering and other operations described below, the amount of information sent to the cloud computing server 62 from the gateway 52”).
7. Regarding Claim 16, Wang discloses The image processing system according to claim 9, wherein the second server is a server of a higher layer that supervises the one or more first servers (Fig. 2: the gateway is explicitly described as a higher-layer server that oversees and manages multiple cameras (first servers) see Col. 10 lines 4-67).
8. Claim 17 is a method claim, rejected with respect to the same limitation rejected in system claim 1.
9. Claim 18 is a non-transitory CRM claim, rejected with respect to the same limitation rejected in system claim 1.
10. Claim(s) 2, 3, 11 is/are rejected under 35 U.S.C. 103 as being unpatentable over Wang in view of Chang as applied to claim 1 above, and further in view of U.S. Patent Application 2019/0335074, Malkes et al. (hereinafter Malkes).
11. Regarding Claim 2, Wang in view of Chang discloses The image processing apparatus according to claim 1,
However, Wang in view of Chang does not explicitly disclose wherein the first image processing includes image correction processing.
Further, Malkes teaches wherein the first image processing includes image correction processing ([0007], [0015], “A camera captures a reference image during a first environmental condition. Environmental information from sensors or a network source identifies a second environmental condition, during which the camera captures an environment-affected image. An environmental effect affecting the environment-affected image is identified based on a difference between the reference image and the environment-affected image” [0052], “At step 610, an action may be initiated to deter or mitigate effect of the environmental conditions on the images captured by the omnidirectional camera”).
It would have been obvious to a person ordinary skill in the art, before the effective filing date of the invention to incorporate the known technique of performing correction processing on the received image using environment sensor data as taught by Malkes into the first image processing stage as taught in Wang, because both references are directed to improving the quality and reliability of images in distributed processing systems. Doing so would yield predictable benefits: normalizing images before transmission ensures that the subsequent (second server) processing is more accurate and consistent.
12. Regarding Claim 3, Wang in view of Chang further in view of Malkes discloses The image processing apparatus according to claim 2,
Further, Malkes discloses wherein the at least one processor is configured to execute the instructions to correct the received image by using sensor information of an environment sensor in the correction processing ([0051], “At step 608, data of environmental conditions may be obtained from a sensor 132 present in the camera unit.” [0017], “The control system 102 eliminates effects of environmental conditions on images, videos, and/or other visual media captured by an omnidirectional camera.” [0024], “he processor 202 may execute an algorithm stored in the memory 214 for eliminating effects of environmental conditions on images captured by the camera.”).
13. Regarding Claim 11, Wang discloses The image processing system according to claim 10,
However, Wang in view of Chang does not explicitly disclose wherein the at least one processor is configured to execute the instructions to correct the received image by using sensor information of an environment sensor in the correction processing.
Further, Malkes teaches wherein the at least one processor is configured to execute the instructions to correct the received image by using sensor information of an environment sensor in the correction processing ([0007], [0015], “A camera captures a reference image during a first environmental condition. Environmental information from sensors or a network source identifies a second environmental condition, during which the camera captures an environment-affected image. An environmental effect affecting the environment-affected image is identified based on a difference between the reference image and the environment-affected image” [0052], “At step 610, an action may be initiated to deter or mitigate effect of the environmental conditions on the images captured by the omnidirectional camera”).
It would have been obvious to a person ordinary skill in the art, before the effective filing date of the invention to incorporate the known technique of performing correction processing on the received image using environment sensor data as taught by Malkes into the first image processing stage as taught in Wang, because both references are directed to improving the quality and reliability of images in distributed processing systems. Doing so would yield predictable benefits: normalizing images before transmission ensures that the subsequent (second server) processing is more accurate and consistent.
14. Claim(s) 4 and 19 are rejected under 35 U.S.C. 103 as being unpatentable over Wang in view of Chang further in view of Malkes as applied to claim 2 above, and further in view of U.S. Patent 9172871, Zhao et al. (hereinafter Zhao).
15. Regarding Claim 4, Wang in view of Chang further in view of Malkes discloses The image processing apparatus according to claim 2,
However, Wang in view of Chang further in view of Malkes discloses wherein the at least one processor is configured to execute the instructions to correct the received image in correspondence with a transmission source of the image in the correction processing.
Further, Zhao teaches wherein the at least one processor is configured to execute the instructions to correct the received image in correspondence with a transmission source of the image in the correction processing (abstract, “acquiring information of independent images that are captured by each camera and have no overlap area or have an overlap area smaller than a threshold; acquiring, according to information of each independent image, an image correction parameter that corresponds to each camera”).
It would have been obvious to a person ordinary skill in the art, before the effective filing date of the invention to combining Wang’s/Chang distributed image processing architecture, the sensor-based image correction as taught in Malkes, and the camera-specific correction techniques of Zhao would normalize differences between cameras in a multi-camera system, ensuring that the images sent on the second server are consistent and comparable. This would in turn enhance performance of the second-stage and third-stage processing described in Wang.
16. Regarding Claim 19, Wang in view of Chang discloses The image processing apparatus according to claim 1,
Chang discloses wherein the processing of adjusting images comprises correcting the images so that at least one of an angle of view of the images (Chang’s “tilt” parameter directly corrects the angular orientation of the captured image relative to the ideal ([0072]-[0074]: “the actual captured image is rotated and displayed compared to the ideal subject… inclined at a certain angle (A-tilt angle)”) or brightness of the images conforms to the predetermined standard .
Chang does not disclose brightness of the images conforms to the predetermined standard
Further, Zhao teaches brightness of the images conforms to the predetermined standard (correcting images from multiple cameras so the are “consistent in geometric position, color, and brightness.” In Col. 1 lines 49-50. This is done by acquiring, for each camera, a “geometric correction parameter and/or a color correction parameter” used to correct brightness/color and geometric position- i.e., adjusting each camera’s image toward a common, predetermined consistency standard across the multi-camera system).
It would have been obvious to one of ordinary skill in the art to combine Zhao’s brightness correction teaching with Wang’s first-tier image processing to ensure consistent, high-quality image output across Wang’s plurality of cameras prior to transmission to the second-tier server.
17. Claim(s) 5 and 6 are rejected under 35 U.S.C. 103 as being unpatentable over Wang in view of Chang as applied to claim 1 above, and further in view of U.S. Patent Application 2023/0060383, MA et al. (hereinafter MA).
18. Regarding Claim 5, Wang in view of Chang discloses The image processing apparatus according to claim 1,
Wang teaches in Col. 6 lines 24-25 “A fixed position camera 12 may be set in a fixed position, such as mounted to the eaves of a building”
However, in view of Chang does not explicitly disclose wherein the at least one processor is configured to execute the instructions to receive an image acquired from a mobile body by using a camera mounted on the mobile body.
Further, MA teaches wherein the at least one processor is configured to execute the instructions to receive an image acquired from a mobile body by using a camera mounted on the mobile body ([0043], “The autonomous driving system 100 may include sensor drivers and a world engine 102 that is configured to capture and process sensor data relating to an environment in which the autonomous vehicle travels”).
It would have been obvious to a person ordinary skill in the art, before the effective filing date of the invention to modify Wang’s distributed image processing architecture to use vehicle mounted cameras as the transmission source as taught in MA yields a system in which Wang’s hierarchical architecture receives images from vehicle cameras, achieving real-time analysis for mobile platforms, and reduce on-board compute load and leverage powerful cloud servers.
19. Regarding Claim 6, Wang in view of Chang further in view of MA discloses The image processing apparatus according to claim 5,
MA discloses wherein the at least one processor is configured to execute the instructions to perform the processing the first image processing by using vehicle information of a mobile body that is a transmission source of the received image ([0043], “The autonomous driving system 100 may include sensor drivers and a world engine 102 that is configured to capture and process sensor data relating to an environment in which the autonomous vehicle travels”).
It would have been obvious to a person ordinary skill in the art, before the effective filing date of the invention to modify Wang’s distributed image processing architecture to use vehicle mounted cameras as the transmission source as taught in MA yields a system in which Wang’s hierarchical architecture receives images from vehicle cameras, achieving real-time analysis for mobile platforms, and reduce on-board compute load and leverage powerful cloud servers.
20. Claim(s) 12 are rejected under 35 U.S.C. 103 as being unpatentable over Wang in view of Chang as applied to claim 10 above, and further in view of U.S. Patent 9172871, Zhao et al. (hereinafter Zhao).
21. Regarding Claim 12, Wang in view of Chang discloses The image processing system according to claim 10,
However, Wang in view of Chang does not explicitly disclose wherein the at least one processor is configured to execute the instructions to correct the received image in correspondence with a transmission source of the image in the correction processing.
Further, Zhao teaches wherein the at least one processor is configured to execute the instructions to correct the received image in correspondence with a transmission source of the image in the correction processing (abstract, “acquiring information of independent images that are captured by each camera and have no overlap area or have an overlap area smaller than a threshold; acquiring, according to information of each independent image, an image correction parameter that corresponds to each camera”).
It would have been obvious to a person ordinary skill in the art, before the effective filing date of the invention to combining Wang’s distributed image processing architecture with the camera-specific correction techniques of Zhao would normalize differences between cameras in a multi-camera system, ensuring that the images sent on the second server are consistent and comparable. This would in turn enhance performance of the second-stage and third-stage processing described in Wang.
22. Claim(s) 13 are rejected under 35 U.S.C. 103 as being unpatentable over Wang in view of Chang as applied to claim 9 above, and further in view of U.S. Patent Application 2022/0232461, Chaysinh et al. (hereinafter Chaysinh).
23. Regarding Claim 13, Wang discloses The image processing system according to claim 9,
However, Wang does not explicitly disclose wherein the first server is a multi-access/mobile edge computing (MEC) server.
Further, Chaysinh teaches wherein the first server is a multi-access/mobile edge computing (MEC) server (claim 1, “multi-access edge computing (MEC) clusters”).
It would have been obvious to a person ordinary skill in the art, before the effective filing date of the invention to implement Wang’s “first server”: as a multi-access edge computing (MEC) server as described in Chaysinh would yield predictable, well-understood advantages: lower latency, reduced backhaul bandwidth, and real-time responsiveness. Hence improvements sought in video surveillance and vehicular applications.
24. Claim(s) 20 is rejected under 35 U.S.C. 103 as being unpatentable over Wang in view of Chang as applied to claim 1 above, and further in view of U.S. Patent Application 2010/0007751 Icho et al. (hereinafter Icho).
25. Regarding Claim 20, Wang in view of Chang discloses The image processing apparatus according to claim 1,
Wang in view of Chang does not explicitly disclose wherein the processing of adjusting images comprises correcting the images so that the angle of view of the images conforms to the predetermined standard by changing an image range of the images and a viewpoint position of the images
Further, Icho teaches wherein the processing of adjusting images comprises correcting the images so that the angle of view of the images conforms to the predetermined standard (Claim 1, “a determination unit operable to determine an output image frame, by correcting a standard image frame in accordance with the acquired positional difference information” -the standard image frame is the predetermined standard, and the output image frame is generated by correcting it) by changing an image range of the images (Fig. 16 shows “(i) a scheduled imaging range to be captured from the scheduled camera position and (ii) an actual imaging range captured from the actual camera position”, [0081]) and a viewpoint position of the images ([0014], “a difference acquisition unit operable to acquire positional difference information indicating a difference between (i) a scheduled camera position in which the camera is scheduled to be positioned… and (ii) an actual camera position in which the camera is positioned”).
It would have been obvious to one of ordinary skill in the art to apply Icho’s position/range-based frame correction technique to Wang’s first-tier image processing in order to ensure each camera’s output conforms to a common predetermined standard prior to transmission to Wang’s second-tier server, with predictable results and a reasonable expectation of success.
Conclusion
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 OMER KHALID whose telephone number is (571)270-5997. The examiner can normally be reached Monday- Friday 9am-7pm.
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/OMER KHALID/Examiner, Art Unit 2422
/JOHN W MILLER/Supervisory Patent Examiner, Art Unit 2422
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