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
Claims 1-20 are pending in this office action.
Information Disclosure Statement
The information disclosure statements (IDS) submitted on January 28, 2026, and March 20, 2026, are in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
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.
Claims 1-20 are rejected under 35 U.S.C. 103 as being unpatentable over Kumar et al. (U.S. Patent No. 10,872,221).
Regarding claims 1, 13, and 17, Kumar et al. teaches a system, comprising: an illumination source comprising a plurality of light-emitting elements, wherein one or more individual ones of the light-emitting elements are configured to be controlled independently of one or more other light-emitting elements to emit light towards one or more biometric aspects (fig. 2 and abstract); a camera configured to capture light reflected from the one or more biometric aspects (fig. 2, ref. num 212); and a controller comprising one or more processors, wherein the controller is configured to (fig. 2, ref. num 220): direct the illumination source to emit light using a plurality of selected configurations for the light emitting elements resulting in the emitted light being emitted according to a plurality of illumination channels (col. 4, lines 16-39); direct the camera to capture respective images of the object when respective ones of the illumination channels are applied (col. 8, lines 42-55); and analyze the respective captured images for use in biometric authentication, wherein the analysis accounts for variations across the respective captured images due to the application of the respective ones of the illumination channels (col. 17, lines 23-35).
Kumar et al. specifically describes hand-based biometrics, whereas the claims are directed towards iris-based biometrics. The specific type of biometric data is an obvious modification that would have been recognized by a person having ordinary skill in the art.
Regarding claims 2 and 14, Kumar et al. teaches wherein the selected plurality of illumination channels comprise particular combinations of the light emitted from the light-emitting elements having selected: wavelength combinations; intensities; and directions (col. 10, lines 62-67).
Regarding claim 3, Kumar et al. teaches wherein to perform the analysis of the respective captured images the controller is further configured to: cause a record to be maintained of an order in which ones of the respective illumination channels are applied when capturing the respective ones of the images; determine whether the variations observed in the respective ones of the images are consistent with the illumination channels applied according to the recorded order (col. 8, line 56 through col. 9, line 14).
Regarding claim 4, Kumar et al. teaches wherein the analysis of the respective captured images is performed using a trained machine learning model (col. 13, lines 26-44).
Regarding claim 5, Kumar et al. teaches wherein the trained machine learning model was trained using a dataset comprising images labeled according to the respective illumination channels at which the respective images were captured (col. 13, lines 26-44).
Regarding claim 6, Kumar et al. teaches wherein to perform the analysis of the respective captured images the controller is further configured to: compare information derived from one or more of the respective captured images to information derived from one or more respective registration images corresponding to a user wherein a same set of illumination channels were applied to the one or more respective captured images and the one or more respective registration images (col. 17, lines 23-35).
Regarding claim 7, Kumar et al. teaches wherein the comparison of the information derived from the one or more respective captured images and the information derived from the one or more respective registration images is performed as part of a user authentication process wherein the user authentication process further comprises an iris-based biometric authentication process (abstract, non-contact biometric).
Regarding claim 8, Kumar et al. teaches wherein information considered in the comparison of the information derived from the one or more of the respective captured images to the information derived from the one or more respective registration images comprises one or more of: information indicating three-dimensional structure of the one or more biometric aspects; reflectivity of the surface of the one or more biometric aspects; and wavelengths of light reflected from the one or more biometric aspects (col. 16, lines 49-57).
Regarding claim 9, Kumar et al. teaches wherein the controller is configured to perform said compare the information derived from the one or more of the respective captured images to the information derived from the one or more respective registration images, in response to: a determination that the variations observed in the information derived from the respective ones of the images are consistent with illumination channels applied according to an order when capturing the respective ones of the images (col. 17, lines 23-35).
Regarding claim 10, Kumar et al. teaches wherein the information derived from one or more of the respective captured images and the information derived from one or more respective registration images is determined by one or more trained machine learning models (col. 13, lines 26-44).
Regarding claim 11, Kumar et al. teaches wherein the system further comprises a head-mounted device (col. 25, lines 16-32).
Regarding claim 12, Kumar et al. teaches wherein the system further comprises: a mobile user device; a vehicle; a stationary device (col. 25, lines 16-32).
Regarding claims 15 and 19, Kumar et al. teaches wherein the analysis of the respective captured images is performed by: selecting respective one or more expected illumination channels based on the respective one or more captured images; and determining whether the respective one or more expected illumination channels are the same as the respective one or more illumination channels applied when the respective one or more images were captured (col. 20, lines 4-15).
Regarding claims 16 and 20, Kumar et al. teaches wherein the analysis of the respective captured images is performed by comparing information derived from one or more of the respective captured images to respective templates corresponding to a user and the respective one or more illumination channels of the respective one or more images (col. 23, lines 48-56).
Regarding claim 18, Kumar et al. teaches further comprising performing a randomization process to select the plurality of illumination configurations (col. 6, lines 43-55 and col. 12, lines 39-57).
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/BRANDON HOFFMAN/Primary Examiner, Art Unit 2433