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 Arguments
Applicant’s arguments filed on August 14, 2025 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.
Claims 1, 15 and 16 are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph according to the amendment received on August 14, 2025.
Response to Amendment
The amendment to the claims received on August 14, 2025 has been entered.
The amendment of claims 1-7, 9, 10, 13-17, 19 and 20 is acknowledged.
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 (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.
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.
Claims 1, 2, 6-7, 10, 13-16 and 18-20 is rejected under 35 U.S.C. 103 as being unpatentable over Cabral’555 (US 2019/0026555), and further in view of Man’697 (US 11,368,697), Prakash’679 (US 7,289,679) and Bourdev’047 (US 2018/0174047).
With respect to claim 1, Cabral’555 teaches an apparatus [regarding to the system shown in Fig.1] comprising:
at least one processor [the system shown in Fig.1 is inherent disclosed with at least one processor to perform its desired functions];
wherein the at least one processor [the system shown in Fig.1 is inherent disclosed with at least one processor to perform its desired functions]:
acquires a captured image [the image can be generated from a camera (paragraph 35). The images are being selected in step 410 in Fig.4];
compresses the captured image to generate a compressed image (Fig.4, step 425);
performs, in response to input of a new captured image, learning processing of a model for outputting a compression parameter value to be applied in compression of the captured image by using learning data including the evaluation, a captured image corresponding to the compressed image targeted for the evaluation, and a compression parameter value applied in generation of the compressed image (paragraphs 51, 60 and Fig.6).
generates a plurality of compressed images different from each other from a same captured image [a multiple compressed images associated with different compression configured are being generated from a training image (Fig. 4, step 425, 430, 435 and 450)];
acquires captured images from a plurality of cameras [multiple cameras might connect to a computer system (paragraph 69)];
Cabral’555 does not teach acquires evaluation of compressed image according to at least one operation input from a user via a terminal indicative of visibility of the compressed image, and acquires a relative evaluation of visibilities among the plurality of compressed image as the evaluation; acquires the evaluation of compressed images for each of the camera; performs learning processing of the model different for each camera; wherein a first model for a first camera of the plurality of cameras is different from a second model for a second camera of the plurality of cameras, the first camera and the second camera situated in a same facility.
Man’697 teaches an evaluation acquisition unit that uses the at least one processor to acquire evaluation of compressed image according to at least one operation input from a user via a terminal indicative of visibility of the compressed image [The image is being compressed according to the configured target quality (Fig.1, step S115 and S120) and the compressed image quality is being inspected and determined (Fig.1, steps 125, 130). The target quality can be desired quality indicated by a user (col.4, lines 13-15). Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention to recognize to use an input device (a terminal) to enable a user to configure the desired target quality for compressing an image because this will allow the desired target quality for the compressed image to be configured more effectively. In addition, the image quality determination result associated with the compressed image is considered being determined according to the target quality configured by a user via input device (a terminal)].
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Cabral’555 according to the teaching of Man’697 to enable a user to configure the desired target quality to compress a captured image because this will allow the captured image to be compressed with desired quality more effectively.
The combination Cabral’555 and Man’697 does not teach acquires a relative evaluation of visibilities among the plurality of compressed image as the evaluation; acquires the evaluation of compressed images for each of the camera; performs learning processing of the model different for each camera; wherein a first model for a first camera of the plurality of cameras is different from a second model for a second camera of the plurality of cameras, the first camera and the second camera situated in a same facility.
Prakash’679 teaches the evaluation acquisition unit uses the at least one processor to acquire a relative evaluation of visibilities among the plurality of compressed image as the evaluation [as shown in Fig. 1, the compressed image is being evaluated to determine its quality is acceptable. Examiner views that the system shown in Fig.1 is cable to perform as many evaluations as wanted for a plurality of compressed images according to a user’s instruction since same image evaluation process allows to perform many times];
acquires the evaluation of compressed images for each of the camera [as shown in Fig. 1, the compressed image is being evaluated to determine its quality is acceptable. Examiner views that the system shown in Fig.1 is cable to perform as many evaluations as wanted for a plurality of compressed images for cameras according to a user’s instruction since same image evaluation process allows to perform many times for cameras]
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify the combination of Cabral’555 and Man’697 according to the teaching of Prakash’679 to include a system to evaluated the quality of the compressed images because this will allow the captured image to be compressed with desired quality more effectively.
The combination of Cabral’555, Man’697 and Prakash’679 does not teach performs learning processing of the model different for each camera; wherein a first model for a first camera of the plurality of cameras is different from a second model for a second camera of the plurality of cameras, the first camera and the second camera situated in a same facility.
Bourdev’047 teaches performs learning processing of the model different for each camera (Fig.4A and paragraphs57- 62);
wherein a first model for a first camera of the plurality of cameras is different from a second model for a second camera of the plurality of cameras, the first camera and the second camera situated in a same facility (Fig.4A and paragraphs 57- 62).
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify the combination of Cabral’555, Man’697 and Prakash’679 according to the teaching of Bourdev’047 to train each encoder for each camera to perform image compression because this will allow each encoder for each camera to provide desired compressed images more effectively.
With respect to claim 2, which further limits claim 1, Cabral’555 teaches the at least one processor to compress the captured image for each area to generate the compressed image (paragraph 46),
acquires the evaluation for at least a partial area of the compressed image (paragraphs 46 and Fig.4, steps 430 and step 435), and
performs, in response to input of a new captured image, learning processing of the model for outputting a compression parameter value to be applied in compression of at least a partial area of the captured image by using learning data including the evaluation for at least a partial area of the compressed image, the at least a partial area targeted for the evaluation in the captured image, and the compression parameter value applied in generation of the at least a partial area (paragraphs 46, 51, 60 and Fig.6).
With respect to claim 6, which further limits claim 1, Cabral’555 teaches the at least one processor acquires the evaluation according to the visibility of the compressed image and smallness of a data amount of the compressed image (paragraphs 47 and 48).
With respect to claim 7, which further limits claim 1, Cabral’555 teaches the at least one processor sequentially generates the compressed image by changing a compression parameter value (paragraph 48).
With respect to claim 10, which further limits claim 1, Cabral’555 teaches the at least one processor performs learning processing of the model such that a compression parameter value to be applied in compression is between a compression parameter value of a compressed image targeted for the evaluation that is positive and a compression parameter value of a compressed image targeted for the evaluation that is negative (paragraph 51).
With respect to claim 13, which further limits claim 1, the combination of Cabral’555 and Man’697 does not teach the at least one processor acquires the evaluation for each user and the at least one processor performs learning processing of the model different for each user.
Since Cabral’555 has suggested that the quality of the compressed image is being determined according to the user’s feedbacks (paragraph 48), therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to recognize to determine the quality of the compressed image according to the users’ feedbacks when multiple users are participating to determine the quality of the compressed image when each user has different quality standard to determine the quality of the compressed image (the at least one processor acquires the evaluation for each user and the at least one processor performs learning processing of the model different for each user) because this will allow the compression parameters to be generated more effectively.
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify the combination of Cabral’555, Man’697, Prakash’679 and Bourdev’047 to determine the quality of the compressed image according to the users’ feedbacks when multiple users are participating to determine the quality of the compressed image when each user has different quality standard to determine the quality of the compressed image (the at least one processor acquires the evaluation for each user and the at least one processor performs learning processing of the model different for each user) because this will allow the compression parameters to be generated more effectively.
With respect to claim 14, which further limits claim 1, the combination of Cabral’555, Man’697, Prakash’679 and Bourdev’047 does not teach the at least one processor performs learning processing of the model common among a plurality of users.
Cabral’555 teaches the compression system is being trained according to the inputted image and user’s feedback (Fig.4 and paragraph 48), and the compression system performs compression on the images after compression system is being trained according to the user’s instructions (Fig.6), therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to recognize to enable the compression system to be trained and used by multiple users (the at least one processor performs learning processing of the model common among a plurality of users) because this will allow the compression system to be trained and used more effectively.
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify the combination of Cabral’555, Man’697, Prakash’679 and Bourdev’047 to enable the compression system to be trained and used by multiple users (the at least one processor performs learning processing of the model common among a plurality of users) because this will allow the compression system to be trained and used more effectively.
With respect to claim 15, which further limits claim 1, Cabral’555 teaches the at least one processor transmits the compressed image to a monitoring terminal, wherein the at least one processor acquires the evaluation via the monitoring terminal [the quality of compressed image is being determined according to the feedback of the user (paragraph 48). Therefore, a transmission unit is considered being disclosed to transmit the compressed image to a monitoring terminal and the evaluation acquisition unit is considered being disclosed to acquire the evaluation via the monitoring terminal when the quality of compressed image is being determined according to the feedback of the user].
With respect to claim 16, which further limits claim 15, Cabral’555 teaches the at least one processor supplies a captured image newly acquired by the image acquisition unit to the model on which learning processing has been performed by the learning processing unit, the at least one processor applies a compression parameter value output from the model in response to supply of a new captured image by the supply unit, and generates a compressed image from the new captured image [the operations shown in Fig.4 are considered being performed multiple times according to the user’s instructions].
With respect to claim 18, which further limits claim 5, Cabral’555 teaches wherein the apparatus is a transcoder disposed between a monitoring camera that captures a captured image and the monitoring terminal [as shown in Fig.4, the input image is being obtained in step 410 first, the inputted image is being perform the compression operation according to the desired compression algorithm and/or a first candidate parameter in step 425 and then the quality of the compressed image is being evaluated in step 430. The input image can be obtained from a camera (paragraph 35) and the quality of the compressed image is being evaluated according to the user feedback (paragraph 48). Therefore, an apparatus is considered being disclosed as a transcoder disposed between a monitoring camera that captures a captured image and the monitoring terminal].
With respect to claim 19, it is a method claim that claims how the apparatus of claim 1 to train the compression operation. Claim 1 is it is analyzed and rejected for the same reason set forth in the rejection of claim 1. In addition, the reference has disclosed an apparatus to train the compression operation, the process (method) to train the compression operation is inherent disclosed to be performed by a processor in the apparatus when the apparatus performs the operation to train the compression operation.
With respect to claim 20, it is a claim regarding to a computer readable medium storing thereon a computer program. Claim 20 claims how the apparatus of claim 1 execute to generate associating information to associate the terminal identifier and the user identifier. Claim 20 is it is analyzed and rejected for the same reason set forth in the rejection of claim 1. In addition, the reference discloses a process, the process would be implemented by a processor that requires a non-transitory computer readable medium, e.g., a RAM, to function, thus, the medium is inherently present.
Claim 3 is rejected under 35 U.S.C. 103 as being unpatentable over Cabral’555 (US 2019/0026555), Man’697 (US 11,368,697), Prakash’679 (US 7,289,679), Bourdev’047 (US 2018/0174047) and further in view of Huang’593 (US 2013/0094593).
With respect to claim 3, which further limits claim 2, the combination of Cabral’555, Man’697, Prakash’679 and Bourdev’047 does not teach the at least one processor acquires the evaluation for an area designated by a user in the compressed image.
Huang’593 teaches that a user designates the regions in an image to perform the compression operation (paragraph 58 and Fig.1).
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify the combination of Cabral’555, Man’697, Prakash’679 and Bourdev’047 according to the teaching of Huang’593 to allow a user to designate a desired region in the input image to perform the compression operation and then to evaluate the result of the compression according the user’s feedback (Fig.4 and Fig.6 in Huang’593) for training the compression configuration in the system (Fig.1, in Huang’593) (the at least one processor acquires the evaluation for an area designated by a user in the compressed image) because this will allow the comparation parameters in a system to be configured more effectively.
Claims 4 and 5 are rejected under 35 U.S.C. 103 as being unpatentable over Cabral’555 (US 2019/0026555), Man’697 (US 11,368,697), Prakash’679 (US 7,289,679), Bourdev’047 (US 2018/0174047) and further in view of Miyazaki’788 (US 2012/0212788).
With respect to claim 4, which further limits claim 1, the combination of Cabral’555, Man’697, Prakash’679 and Bourdev’047 does not teach the at least one processor acquires an operation for enlarging and displaying the compressed image as the evaluation that is negative for at least an enlarged area of the compressed image.
Miyazaki’788 teaches that a special program displaying the image data by enlarging the compressed image (paragraph 36).
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify the combination of Cabral’555, Man’697, Prakash’679 and Bourdev’047 according to the teaching of Miyazaki’788 to include a special program to display the image data by enlarging the compressed image to enable the user to evaluate if the quality of the compressed image is acceptable according to the enlarged compressed image (the at least one processor acquires an operation for enlarging and displaying the compressed image as the evaluation that is negative for at least an enlarged area of the compressed image) because this will allow the quality of the compressed image data to be determined by a user more effectively.
With respect to claim 5, which further limits claim 1, the combination of Cabral’555, Man’697, Prakash’679 and Bourdev’047 does not teach the at least one processor acquires an operation for displaying a displayed compressed image again as the evaluation that is negative for the compressed image.
Miyazaki’788 teaches that a special program displaying the image data by enlarging the compressed image (paragraph 36).
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify the combination of Cabral’555, Man’697, Prakash’679 and Bourdev’047 according to the teaching of Miyazaki’788 to display the image data by enlarging the compressed image in a special program as many time as a user wants enable the user to evaluate if the quality of the compressed image is acceptable according to the enlarged compressed image (the at least one processor acquires an operation for displaying a displayed compressed image again as the evaluation that is negative for the compressed image) because this will allow the quality of the compressed image data to be determined by a user more effectively.
Claim 9 is rejected under 35 U.S.C. 103 as being unpatentable over Cabral’555 (US 2019/0026555), Man’697 (US 11,368,697), Prakash’679 (US 7,289,679), Bourdev’047 (US 2018/0174047) and further in view of Malkes’074 (US 2019/0335074).
With respect to claim 9, which further limits claim 1, the combination of Cabral’555, Man’697, Prakash’679 and Bourdev’047 does not teach the at least one processor acquires, as the captured image, an image which is captured under a reference imaging condition and to which an image effect according to another imaging condition different from the reference imaging condition is applied, the at least one processor generates the compressed image by applying an image effect according to the reference imaging condition to the captured image, and the at least one processor acquires the evaluation according to the visibility of the compressed image and a degree of approximation of the compressed image and the image captured under the reference imaging condition.
Malkes’074 teaches the at least one processor acquires, as the captured image, an image which is captured under a reference imaging condition and to which an image effect according to another imaging condition different from the reference imaging condition is applied [the image captured by a camera having a reference image condition and an image effect (paragraph 50, 52 and 55)],
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify the combination of C Cabral’555, Man’697, Prakash’679 and Bourdev’047 according to the teaching of Miyazaki’788 to include a camera to generate the images having reference image condition and an image effect for generating the desired compression parameters because this will allow the compression parameters to be generated more effectively.
The combination of Cabral’555, Man’697, Prakash’679, Bourdev’047 and Malkes’074 does not teach the at least one processor generates the compressed image by applying an image effect according to the reference imaging condition to the captured image, and the at least one processor acquires the evaluation according to the visibility of the compressed image and a degree of approximation of the compressed image and the image captured under the reference imaging condition.
Since Cabral’555 teaches that the content category of the inputted images are being are being identified, and the desired candidate compression algorithm and/or parameter algorithm are being selecting to generate the compressed image, and then the quality and the size reduction of the generated compressed image are being examined according to the user’s feedback (Fig.4 and paragraph 48), and Malkes’074 teaches that the image captured by a camera having a reference image condition and an image effect (paragraph 50, 52 and 55), therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to recognize to provide the images captured by a camera having a reference image condition and an image effect as the inputted images and then to identify the content category of the said inputted images generated from the said camera including the image effects such that the desired candidate compression algorithm and/or parameter algorithm are being selecting to generate the compressed image to enable the quality and the size reduction of the generated compressed image to be examined according to the user’s feedback (the at least one processor generates the compressed image by applying an image effect according to the reference imaging condition to the captured image, and the at least one processor acquires the evaluation according to the visibility of the compressed image and a degree of approximation of the compressed image and the image captured under the reference imaging condition) because this will allow the compression parameters to be generated more effectively.
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify the combination of Cabral’555, Man’697, Prakash’679, Bourdev’047 and Malkes’074 to provide the images captured by a camera having a reference image condition and an image effect as the inputted images and then to identify the content category of the said inputted images generated from the said camera including the image effects such that the desired candidate compression algorithm and/or parameter algorithm are being selecting to generate the compressed image to enable the quality and the size reduction of the generated compressed image to be examined according to the user’s feedback (the at least one processor generates the compressed image by applying an image effect according to the reference imaging condition to the captured image, and the at least one processor acquires the evaluation according to the visibility of the compressed image and a degree of approximation of the compressed image and the image captured under the reference imaging condition) because this will allow the compression parameters to be generated more effectively.
Claim 17 is rejected under 35 U.S.C. 103 as being unpatentable over Cabral’555 (US 2019/0026555), Man’697 (US 11,368,697), Prakash’679 (US 7,289,679), Bourdev’047 (US 2018/0174047) and further in view of Lee’261 (US 2004/0131261) and Torres’282 (US 6,564,282)
With respect to claim 17, which further limits claim 16, the combination of Cabral’555, Man’697, Prakash’679 and Bourdev’047 does not teach the at least one processor generates the compressed image by applying an image effect according to a reference imaging condition to a captured image captured under another imaging condition different from the reference imaging condition, and the at least one processor transmits the compressed image and identification information indicating the another imaging condition to the monitoring terminal.
Lee’261 teaches the at least one processor generates the compressed image by applying an image effect according to a reference imaging condition to a captured image captured under another imaging condition different from the reference imaging condition [the image is being added with desired effect and then it is being compressed (paragraph 68)].
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify the combination of Cabral’555, Man’697, Prakash’679 and Bourdev’047 according to the teaching of Lee’261 to compress an inputted image by applying an image effect to the said inputted image because this will allow the desired compered image to be generated more effectively.
The combination of Cabral’555, Man’697, Prakash’679, Bourdev’047 and Lee’261 does not teach the at least one processor transmits the compressed image and identification information indicating the another imaging condition to the monitoring terminal.
Torres’282 teaches that the image file includes image tags information for identifying the image data (Fig.5).
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify the combination of Cabral’555, Man’697, Prakash’679, Bourdev’047 and Lee’261 according to the teaching of Torres’282 to include the image tags information in the compressed image data including the information regarding to the image condition and then to transmit it to a user’s device for obtaining the quality feedback related to the compressed image data from the user (the at least one processor transmits the compressed image and identification information indicating the another imaging condition to the monitoring terminal) because this will allow the user to give the quality feedback related to the compressed image data more effectively.
Conclusion
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 extension fee 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 date of this final action.
Contact
Any inquiry concerning this communication or earlier communications from the examiner should be directed to HUO LONG CHEN whose telephone number is (571)270-3759. The examiner can normally be reached on M-F 9am - 5pm. If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Tieu, Benny can be reached on (571) 272-7490. The fax phone number for the organization where this application or proceeding is assigned is (571) 273-8300. Information regarding the status of an application may be obtained from the Patent Application Information Retrieval (PAIR) system. Status information for published applications may be obtained from either Private PAIR or Public PAIR. Status information for unpublished applications is available through Private PAIR only. For more information about the PAIR system, see http://pair-direct.uspto.gov. Should you have questions on access to the Private PAIR system, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative or access to the automated information system, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/HUO LONG CHEN/Primary Examiner, Art Unit 2682