# US 2021/0279469 A1 · Image signal provenance attestation > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 2021/0279469 A1 - Document ID: US20210279469A1 - Status: Published application - Kind: A1 - Application number: 16/810,720 - Filed: 2020-03-05 - Published: 2021-09-09 - Earliest claimed: 2020-03-05 - Assignees: QUALCOMM Incorporated - Applicants: QUALCOMM Incorporated - Inventors: Wesley James Holland - Web page: https://patentgrep.com/patent/US20210279469A1 ## CPC - G06F 21/64: Protecting data integrity, e.g. using checksums, certificates or signatures - G06F 18/2155: {characterised by the incorporation of unlabelled data, e.g. multiple instance learning [MIL], semi-supervised techniques using expectation-maximisation [EM] or naïve labelling} - G06V 10/141: Control of illumination - G06V 10/462: {Salient features, e.g. scale invariant feature transforms [SIFT]} - G06V 10/764: using classification, e.g. of video objects - G06V 20/30: in albums, collections or shared content, e.g. social network photos or video - G06V 20/647: {by matching two-dimensional images to three-dimensional objects} - H04N 13/271: wherein the generated image signals comprise depth maps or disparity maps - H04N 23/45: for generating image signals from two or more image sensors being of different type or operating in different modes, e.g. with a CMOS sensor for moving images in combination with a charge-coupled device [CCD] for still images - H04N 23/64: {Computer-aided capture of images, e.g. transfer from script file into camera, check of taken image quality, advice or proposal for image composition or decision on when to take image} - H04N 23/672: {based on the phase difference signals} - H04N 23/673: {based on contrast or high frequency components of image signals, e.g. hill climbing method} - H04N 23/71: Circuitry for evaluating the brightness variation - H04N 23/72: Combination of two or more compensation controls - G06V 2201/10: Recognition assisted with metadata - G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N) - G06V: IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING - H04N: PICTORIAL COMMUNICATION, e.g. TELEVISION ## Abstract A computing device is configured to determine the provenance of an image. The computing device may receive an image. The computing device may generate an image capture profile associated with the image based at least in part on data generated during an image capture process. The computing device may determine whether the image is an authentic image based at least in part on the image capture profile. The computing device may, in response to determining that the image is an authentic image, generate a digital signature associated with the image. ## Claims ### Claim 1 An apparatus configured for camera processing, the apparatus comprising: a memory; and processing circuitry in communication with the memory and configured to: receive a first image; generate an image capture profile associated with the first image based at least in part on data generated during an image capture process, wherein the data is based on a sequence of one or more images received prior to the first image; determine whether the first image is an authentic image based at least in part on the image capture profile; and in response to determining that the first image is an authentic image, generate a digital signature associated with the first image. ### Claim 2 (depends on 1) The apparatus of claim 1, wherein to generate the image capture profile, the processing circuitry is further configured to: determine camera sensor metrics associated with a current operating point of a camera sensor; determine, out of a plurality of camera sensor profiles associated with a plurality of different operating points, a camera sensor profile associated with an operating point that corresponds to the current operating point of the camera sensor; and generate the image capture profile based at least in part on comparing the camera sensor metrics with the camera sensor profile. ### Claim 3 (depends on 1) The apparatus of claim 1, wherein to generate the image capture profile, the processing circuitry is further configured to: determine a disparity map of the first image based at least in part on phase information of the first image determined using one or more phase-detection auto focus (PDAF) sensors of a camera sensor; extract a first set of features from the disparity map of the first image; extract a second set of features from the first image captured by the camera sensor; compare the first set of features and the second set of features to determine one or more matching features between the first set of features and the second set of features; and generate the image capture profile based at least in part on the one or more matching features between the first set of features and the second set of features. ### Claim 4 (depends on 1) The apparatus of claim 1, wherein to generate the image capture profile, the processing circuitry is further configured to: determine a sequence of contrast statistics associated with the image capture process; determine a sequence of auto focus commands associated with the image capture process; and generate the image capture profile based at least in part on the sequence of contrast statistics and the sequence of auto focus commands. ### Claim 5 (depends on 1) The apparatus of claim 1, wherein to generate the image capture profile, the processing circuitry is further configured to: determine a sequence of brightness statistics associated with the image capture process; determine a sequence of auto exposure commands associated with the image capture process; and generate the image capture profile based at least in part on the sequence of brightness statistics and the sequence of auto exposure commands. ### Claim 6 (depends on 1) The apparatus of claim 1, wherein to generate the image capture profile, the processing circuitry is further configured to: extract a set of features from the first image; extract an additional set of features from an additional image captured by an additional camera sensor; compare the set of features and the additional set of features to determine one or more matching features between the set of features and the additional set of features; and generate the image capture profile based at least in part on the one or more matching features. ### Claim 7 (depends on 1) The apparatus of claim 1, wherein to generate the image capture profile, the processing circuitry is further configured to: determine one or more data bundles associated with capturing the first image, each of the one or more data bundles including at least two or more of: camera sensor metrics associated with an operating point of a camera sensor associated with capturing the first image, camera sensor metadata associated with the camera sensor, a sequence of auto focus commands associated with capturing the first image, a sequence of auto exposure commands associated with capturing the first image, or an additional set of features from an additional image captured by an additional camera sensor; and generate the image capture profile using a deep neural network based at least in part on the one or more data bundles. ### Claim 8 (depends on 1) The apparatus of claim 1, wherein to determine whether the first image is an authentic image based at least in part on the image capture profile, the processing circuitry is further configured to: determine whether the first image is an authentic image using one of: a machine learning classification model or an unsupervised anomaly detection algorithm ### Claim 9 (depends on 1) The apparatus of claim 1, wherein to generate the digital signature associated with the first image, the processing circuitry is further configured to: determine whether all portions of a camera pipeline are trusted; and generate the digital signature associated with the first image in response to determining that all portions of the camera pipeline are trusted. ### Claim 10 (depends on 1) The apparatus of claim 1, wherein to generate the digital signature associated with the first image, the processing circuitry is further configured to: generate the digital signature that is associated with the first image and with image metadata associated with the first image. ### Claim 11 A method comprising: receiving a first image; generating an image capture profile associated with the first image based at least in part on data generated during an image capture process, wherein the data is based on a sequence of one or more images received prior to the first image; determining whether the first image is an authentic image based at least in part on the image capture profile; and in response to determining that the first image is an authentic image, generating a digital signature associated with the first image. ### Claim 12 (depends on 11) The method of claim 11, wherein generating the image capture profile comprises: determining camera sensor metrics associated with a current operating point of a camera sensor; determining, out of a plurality of camera sensor profiles associated with a plurality of different operating points, a camera sensor profile associated with an operating point that corresponds to the current operating point of the camera sensor; and generating the image capture profile based at least in part on comparing the camera sensor metrics with the camera sensor profile. ### Claim 13 (depends on 11) The method of claim 11, wherein generating the image capture profile comprises: determining a disparity map of the first image based at least in part on phase information of the first image determined using one or more phase-detection auto focus (PDAF) sensors of a camera sensor; extracting a first set of features from the disparity map of the first image; extracting a second set of features from the first image captured by the camera sensor; comparing the first set of features and the second set of features to determine one or more matching features between the first set of features and the second set of features; and generating the image capture profile based at least in part on the one or more matching features between the first set of features and the second set of features. ### Claim 14 (depends on 11) The method of claim 11, wherein generating the image capture profile comprises: determining a sequence of contrast statistics associated with the image capture process; determining a sequence of auto focus commands associated the image capture process; and generating the image capture profile based at least in part on the sequence of contrast statistics and the sequence of auto focus commands. ### Claim 15 (depends on 11) The method of claim 11, wherein generating the image capture profile comprises: determining a sequence of brightness statistics associated with the image capture process; determining a sequence of auto exposure commands associated the image capture process; and generating the image capture profile based at least in part on the sequence of brightness statistics and the sequence of auto exposure commands. ### Claim 16 (depends on 11) The method of claim 11, wherein generating the image capture profile comprises: extracting a set of features from the first image; extracting an additional set of features from an additional image captured by an additional camera sensor; comparing the set of features and the additional set of features to determine one or more matching features between the set of features and the additional set of features; and generating the image capture profile based at least in part on the one or more matching features. ### Claim 17 (depends on 11) The method of claim 11, wherein generating the image capture profile comprises: determining one or more data bundles associated with capturing the first image, each of the one or more data bundles including at least two or more of: camera sensor metrics associated with an operating point of a camera sensor associated with capturing the first image, camera sensor metadata associated with the camera sensor, a sequence of auto focus commands associated with capturing the first image, a sequence of auto exposure commands associated with capturing the first image, or an additional set of features from an additional image captured by an additional camera sensor; and generating the image capture profile using a deep neural network based at least in part on the one or more data bundles. ### Claim 18 (depends on 11) The method of claim 11, wherein determining whether the first image is an authentic image based at least in part on the image capture profile comprises: determining whether the first image is an authentic image using one of: a machine learning classification model or an unsupervised anomaly detection algorithm. ### Claim 19 (depends on 11) The method of claim 11, further comprising: determining whether all portions of a camera pipeline are trusted, wherein generating the digital signature associated with the first image is further in response to determining that all portions of the camera pipeline are trusted. ### Claim 20 (depends on 11) The method of claim 11, wherein generating the digital signature associated with the first image further comprises generating the digital signature that is associated with the first image and with image metadata associated with the first image. ### Claim 21 A non-transitory computer-readable storage medium storing instructions that, when executed, cause one or more processors to: receive a first image; generate an image capture profile associated with the first image based at least in part on data generated during an image capture process, wherein the data is based on a sequence of one or more images received prior to the first image; determine whether the first image is an authentic image based at least in part on the image capture profile; and in response to determining that the first image is an authentic image, generate a digital signature associated with the first image. ### Claim 22 (depends on 21) The non-transitory computer-readable storage medium of claim 21, wherein the instructions that, when executed, cause the one or more processors to generate the image capture profile further cause the one or more processors to: determine camera sensor metrics associated with a current operating point of a camera sensor; determine, out of a plurality of camera sensor profiles associated with a plurality of different operating points, a camera sensor profile associated with an operating point that corresponds to the current operating point of the camera sensor; and generate the image capture profile based at least in part on comparing the camera sensor metrics with the camera sensor profile. ### Claim 23 (depends on 21) The non-transitory computer-readable storage medium of claim 21, wherein the instructions that, when executed, cause the one or more processors to generate the image capture profile further cause the one or more processors to: determine a disparity map of the first image based at least in part on phase information of the first image determined using one or more phase-detection auto focus (PDAF) sensors of a camera sensor; extract a first set of features from the disparity map of the first image; extract a second set of features from the first image captured by the camera sensor; compare the first set of features and the second set of features to determine one or more matching features between the first set of features and the second set of features; and generate the image capture profile based at least in part on the one or more matching features between the first set of features and the second set of features. ### Claim 24 (depends on 21) The non-transitory computer-readable storage medium of claim 21, wherein the instructions that, when executed, cause the one or more processors to generate the image capture profile further cause the one or more processors to: determine a sequence of contrast statistics associated with the image capture process; determine a sequence of auto focus commands associated with the image capture process; and generate the image capture profile based at least in part on the sequence of contrast statistics and the sequence of auto focus commands. ### Claim 25 (depends on 21) The non-transitory computer-readable storage medium of claim 21, wherein the instructions that, when executed, cause the one or more processors to generate the image capture profile further cause the one or more processors to: determine a sequence of brightness statistics associated with the image capture process; determine a sequence of auto exposure commands associated with the image capture process; and generate the image capture profile based at least in part on the sequence of brightness statistics and the sequence of auto exposure commands. ### Claim 26 (depends on 21) The non-transitory computer-readable storage medium of claim 21, wherein the instructions that, when executed, cause the one or more processors to generate the image capture profile further cause the one or more processors to: extract a set of features from the first image; extract an additional set of features from an additional image captured by an additional camera sensor; compare the set of features and the additional set of features to determine one or more matching features between the set of features and the additional set of features; and generate the image capture profile based at least in part on the one or more matching features. ### Claim 27 (depends on 21) The non-transitory computer-readable storage medium of claim 21, wherein the instructions that, when executed, cause the one or more processors to generate the image capture profile further cause the one or more processors to: determine one or more data bundles associated with capturing the first image, each of the one or more data bundles including at least two or more of: camera sensor metrics associated with an operating point of a camera sensor associated with capturing the first image, camera sensor metadata associated with the camera sensor, a sequence of auto focus commands associated with capturing the first image, a sequence of auto exposure commands associated with capturing the first image, or an additional set of features from an additional image captured by an additional camera sensor; and generate the image capture profile using a deep neural network based at least in part on the one or more data bundles. ### Claim 28 (depends on 21) The non-transitory computer-readable storage medium of claim 21, wherein the instructions that, when executed, cause the one or more processors to determine whether the image is an authentic image based at least in part on the image capture profile further cause the one or more processors to: determine whether the first image is an authentic image using one of: a machine learning classification model or an unsupervised anomaly detection algorithm. ### Claim 29 (depends on 21) The non-transitory computer-readable storage medium of claim 21, wherein the instructions that, when executed, cause the one or more processors to generate the digital signature associated with the image further cause the one or more processors to: determine whether all portions of a camera pipeline are trusted; and generate the digital signature associated with the first image in response to determining that all portions of the camera pipeline are trusted. ### Claim 30 (depends on 21) The non-transitory computer-readable storage medium of claim 21, wherein the instructions that, when executed, cause the one or more processors to generate the digital signature associated with the first image further cause the one or more processors to: generate the digital signature that is associated with the first image and with image metadata associated with the first image. ### Claim 31 (depends on 1) The apparatus of claim 1, wherein the processing circuitry is further configured to store the first image, digital signature, and image metadata associated with the first image in response to determining that the first image is an authentic image. ### Claim 32 (depends on 2) The apparatus of claim 2, wherein the camera sensor metrics include one or more of a frame time, a horizontal blanking interval time, a line time, and a vertical blanking interval time. ### Claim 33 (depends on 11) The method of claim 11, further comprising: storing the first image, digital signature, and image metadata associated with the first image in response to determining that the first image is an authentic image. ### Claim 34 (depends on 12) The method of claim 12, wherein the camera sensor metrics include one or more of a frame time, a horizontal blanking interval time, a line time, and a vertical blanking interval time.