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 .
Notice for all Patent Application as subject to AIA
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.
RESPONSE TO AMENDMENT
Amended claims 1-2, 4-18, and 20 are pending and remain for further examination.
The New Grounds of Rejection
Applicants’ amendments and arguments with respect to the claims 1-2, 4-18, and 20 filed on July 22, 2026, have been fully considered. However, upon further consideration, a new ground(s) of rejection is made in view of new references. Applicants’ amendment necessitated the new grounds of rejection.
Claim Rejections - 35 USC § 103
The text of those sections of title AIA 35 U.S.C. 103 code not included in this action can be found in a prior Office Action.
Claims 1-2, 4-18, and 20 are rejected under AIA 35 U.S.C. 103 as being un-patentable over Saito et al (U.S. Patent Application Publication No. 2024/0153326 A1) in view of Koppal et al (U.S. Patent Application Publication 2018/0143430 A1).
As to claim 1, Saito et al disclose an access control management system, configured to control opening of a gate, or entry and exit of an entrance (figure 3, pars. 0071-0072, reference disclose an entry control system), the access control management system comprising: an image capture device, disposed at the gate or the entrance, configured to capture a face image of a user to be identified (figure 3, par. 0073, the entry control system including an image-capturing device); a display, disposed at the gate or the entrance (see figure 3); and a processing device, coupled to the image capture device and the display, and configured to verify an identity of the user, and control the opening of the gate or the entry and exit of the entrance according to a verification result, wherein the first deep learning model identities of a plurality of users registered in advance (figure 2, pars. 0061-0064, figure 3, pars. 0071-0074, figure 4, pars. 0087-0088, figures 5-6, pars. 0095-0097, authentication/unlocking control units verify the user and control the operations of the gate, and register unit identify previously registered users).
However, Saito et al do not teach that de-identify the face image to obtain de-identified image data, and convert the de-identified image data into a plurality of de-identified features for subsequent output; and a processing device configured to receive the de-identified features output by the image capture device, display the de-identified image data on the display without storing the face image, verify an identity of the user to which the de-identified features belong by a trained first deep learning model.
Koppal et al teach that de-identify the face image to obtain de-identified image data and convert the de-identified image data into a plurality of de-identified features for subsequent output (figure 1, pars. 0042-0044, figures 11A-11B, pars. 0080-0082, obtaining de-identified face image data and generating sequence of images); and a processing device configured to receive the de-identified features output by the image capture device, display the de-identified image data on the display without storing the face image, verify an identity of the user to which the de-identified features belong by a trained first deep learning model (figures 2F-2G, pars. 0052-0053, figures 5B-5C, pars. 0072-0073, displaying/providing de-identified image data without storing original face image on the memory).
It would have been obvious to one of ordinary skill in the art before the effective filling date of the claimed invention to incorporate the teaching of Koppal et al as stated above with the access control management system of Saito et al for displaying/providing de-identified image data without storing original face image to on the memory because it would have improved security of user profile and network data and also improved throughput and system utilization by utilizing proper control/authentication devices more efficiently.
As to claim 2, Koppal et al disclose that the image capture device comprises: a lens; an image sensor, configured to sense light intensity passing through the lens to generate an image of a photographed object; an image signal processor, configured to capture the face image in the image (figures 4s-5s, par. 0062, figure 6s, par. 0076, the image capture device captures the face image using lens and sensor), de-identify the face image to obtain the de-identified image data and convert the de-identified image data into the plurality of de-identified features; and an input/output (I/O) interface, configured to output the de-identified features (figures 2F-2G, pars. 0052-0053, figures 5B-5C, pars. 0072-0073, displaying/providing de-identified image data).
It would have been obvious to one of ordinary skill in the art before the effective filling date of the claimed invention to incorporate the teaching of Koppal et al as stated above with the access control management system of Saito et al for displaying/providing de-identified image data without storing original face image to on the memory because it would have improved security of user profile and network data and also improved throughput and system utilization by utilizing proper control/authentication devices more efficiently.
As to claim 4, Saito et al disclose that the processing device further comprises a first communication device configured to communicate with the image capture device or connect to a network; and the image capture device further comprises a second communication device configured to communicate with the first communication device or connect to the network (figure 3).
As to claim 5, Saito et al disclose that an interface device, configured to connect the image capture device and the processing device (figure 3, pars. 0072-0074, figure 4, pars. 0089-0091).
As to claim 6, Koppal et al disclose that the first deep learning model is implemented by an application programming interface (API) attached to a processor of the processing device (figure 3, pars. 0059-0060, figure 16, par. 0107).
As to claims 7-8, Koppal et al disclose that the image signal processor comprises de-identifying the face image by a second deep learning model supporting privacy protection technology, wherein the second deep learning model comprises a plurality of neurons divided into a plurality of layers, the image signal processor converts the face image into feature values of a plurality of neurons in a first layer among the layers, inputs the converted feature values of each of the neurons to a next layer after adding noise generated by using a privacy parameter, and obtains the de-identified image data after processing the layers (figure 1, pars. 0044-0046, figure 3, pars. 0057-0060, obtaining de-identified image data and generating a response).
It would have been obvious to one of ordinary skill in the art before the effective filling date of the claimed invention to incorporate the teaching of Koppal et al as stated above with the access control management system of Saito et al for displaying/providing de-identified image data without storing original face image to on the memory because it would have improved security of user profile and network data and also improved throughput and system utilization by utilizing proper control/authentication devices more efficiently.
As to claims 9-10, Koppal et al disclose that the first deep learning model comprises calculating a similarity between the de-identified features and a feature space established using the de-identified features of each of the users registered in advance, to verify the identity of the user to which the de-identified features belong according to the calculated similarity; and the image capture device is further configured to identify a living body in the face image by a living body recognition technology, and de-identify the face image when the living body is identified in the face image, wherein the living body recognition technology comprises blink detection, deep learning features, challenge-response technology, or a three-dimensional camera (figure 3. Par. 0057, figure 5s, pars. 0062 & 0072, figures 12s, pars. 0100-0101, calculating a similarity between the de-identified features and verifying the identity of the user to which the de-identified features belong according to the calculated similarity).
It would have been obvious to one of ordinary skill in the art before the effective filling date of the claimed invention to incorporate the teaching of Koppal et al as stated above with the access control management system of Saito et al for displaying/providing de-identified image data without storing original face image to on the memory because it would have improved security of user profile and network data and also improved throughput and system utilization by utilizing proper control/authentication devices more efficiently.
As to claims 11-16, they are also rejected for the same reasons set forth to rejecting claims 1-2 and 4-10 above, since claims 11-16 do not teach or define any new limitations than rejected claims 1-2 and 4-10.
As to claims 17-18 and 20, they are also rejected for the same reasons set forth to rejecting claims 1 and 7-8 above, since claims 17-18 and 20 do not teach or define any new limitations than above rejected claims 1 and 7-8.
Response to Arguments
Applicants’ arguments with respect to the claims 1-2, 4-18, and 20 filed on February 26, 2026, have been fully considered but they are deemed to be moot in a new ground(s) of rejection is made in view of new references. The examiner has attempted to answer (response) to the remarks (arguments) in the body of the Office Action (see modified rejection of claims 1-10).
Applicants’ amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicants are reminded of the extension of time policy as set forth in 37 CFR 1.136(a). A shortened statutory period for replying 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.
Additional References
The examiner as of general interest cites the following references.
Peake et al, U.S. Patent No. 12,705,390 B2.
Tsou, U.S. Patent No. 12,519,647 B2.
Perry et al, U.S. Patent No. 11,893,828 B2.
Content Information
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/BHARAT BAROT/Primary Examiner, Art Unit 2453September 18, 2026
