# US 2019/0318154 A1 · Methods, systems, and media for evaluating images > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 2019/0318154 A1 - Document ID: US20190318154A1 - Status: Published application - Kind: A1 - Application number: 16/455,824 - Filed: 2019-06-28 - Published: 2019-10-17 - Earliest claimed: 2016-12-28 - Assignees: Zhejiang Dahua Technology Co., Ltd. - Applicants: Zhejiang Dahua Technology Co., Ltd. - Inventors: Siyu GUO; Haiyang WANG; Jingsong HAO; Gang WANG - Web page: https://patentgrep.com/patent/US20190318154A1 ## CPC - G06V 40/161: {Detection; Localisation; Normalisation} - G06V 10/431: {Frequency domain transformation; Autocorrelation} - G06V 10/993: {Evaluation of the quality of the acquired pattern} - G06V 40/167: {using comparisons between temporally consecutive images} - G06V 10/467: {Encoded features or binary features, e.g. local binary patterns [LBP]} - G06V: IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING ## Abstract A method may include obtaining an image including a face. The method may further include determining at least one time domain feature related to the face in the image and at least one frequency domain information related to the face in the image. The method may further include evaluating the quality of the image based on the at least one time domain feature and the frequency domain information. ## Claims ### Claim 1 A face recognition electronic system, comprising: one or more image obtaining units configured to obtain an image; one or more image processing units connected to the one or more image obtaining units, wherein during operation the one or more image processing units: obtain an image including a face; determine at least one time domain feature related to the face in the image; determine at least one frequency domain information related to the face in the image; evaluate a quality of the image based on the at least one time domain feature and the frequency domain information. ### Claim 2 (depends on 1) The system of claim 1, wherein to evaluate the quality of the image, the one or more image processing units: determine whether the at least one time domain feature satisfies a condition; in response to a determination that the at least one time domain feature satisfies the condition, evaluate the quality of the image based on the frequency domain information. ### Claim 3 (depends on 1) The system of claim 1, wherein the at least one time domain feature related to the face includes at least one of a posture of the face, or a definition of the face in the image. ### Claim 4 (depends on 3) The system of claim 3, wherein to determine the definition of the face in the image, the one or more image processing units: extract at least one landmark point in the image, the at least one landmark point being with respect to a region of interest of the face; determine at least one neighboring point of the at least one landmark point; and determine, based on the at least one landmark point and the at least one neighboring point, a local variance related to the at least one landmark point, an average gradient related to the at least one landmark point, or an edge width related to the at least one landmark point in the image. ### Claim 5 (depends on 4) The system of claim 4, wherein to evaluate the quality of the image, the one or more image processing units: determine a value of a first parameter, the first parameter related to an average edge width of the at least one landmark point and a contrast ratio of the image; determine a value of a second parameter, the second parameter related to the posture of the face; and determine a quality evaluation value of the image based on the value of the first parameter and the value of the second parameter. ### Claim 6 (depends on 1) The system of claim 1, wherein to determine the at least one time domain feature of the face, the one or more image processing units: determine a rotational angel of the face with respect to an axis. ### Claim 7 (depends on 1) The system of claim 1, wherein to determine the at least one time domain feature of the face, the one or more image processing units: determine a confidence value of the face, the confidence value indicating whether the face is occluded. ### Claim 8 (depends on 1) The system of claim 1, wherein to determine the at least one frequency domain information of the image, the one or more image processing units: perform a time-to-frequency-domain transformation on one or more pixel values of the image; weight the time-to-frequency-domain transformed one or more pixel values of the image based on a weighting matrix; and determine the at least one frequency domain information of the image based on the weighted pixel values of the image. ### Claim 9 A method implemented on at least one image processing electronic device, the method comprising: obtaining an image including a face; determining at least one time domain feature related to the face in the image; determining at least one frequency domain information related to the face in the image; evaluating a quality of the image based on the at least one time domain feature and the frequency domain information. ### Claim 10 (depends on 9) The method of claim 9, wherein the evaluating of the quality of the image includes: determining whether the at least one time domain feature satisfies a condition; in response to a determination that the at least one time domain feature satisfies the condition, evaluating the quality of the image based on the frequency domain information. ### Claim 11 (depends on 9) The method of claim 9, wherein the at least one time domain feature related to the face includes at least one of a posture of the face, or a definition of the face in the image. ### Claim 12 (depends on 11) The method of claim 11, wherein the determining of the definition of the face in the image includes: extracting at least one landmark point in the image, the at least one landmark point being with respect to a region of interest of the face; determining at least one neighboring point of the at least one landmark point; and determining, based on the at least one landmark point and the at least one neighboring point, a local variance related to the at least one landmark point, an average gradient related to the at least one landmark point, or an edge width related to the at least one landmark point in the image, ### Claim 13 (depends on 12) The method of claim 12, wherein the evaluating of the quality of the image includes: determining a value of a first parameter, the first parameter related to an average edge width of the at least one landmark point and a contrast ratio of the image; determining a value of a second parameter, the second parameter related to the posture of the face; and determining a quality evaluation value of the image based on the value of the first parameter and the value of the second parameter. ### Claim 14 (depends on 9) The method of claim 9, wherein the determining of the at least one time domain feature of the face includes: determining a rotational angel of the face with respect to an axis. ### Claim 15 (depends on 9) The method of claim 9, wherein the determining of the at least one time domain feature of the face includes: determining a confidence value of the face, the confidence value indicating whether the face is occluded. ### Claim 16 (depends on 9) The method of claim 9, wherein the determining of the at least one frequency domain information of the image includes: performing a time-to-frequency-domain transformation on one or more pixel values of the image; weighting the time-to-frequency-domain transformed one or more pixel values of the image based on a weighting matrix; and determining the at least one frequency domain information of the image based on the weighted pixel values of the image. ### Claim 17 A face recognition electronic system, comprising: one or more image obtaining units configured to obtain an image; one or more image processing units connected to the one or more image obtaining units, wherein during operation the one or more image processing units: obtain a two-dimensional (2D) image including a face, and three-dimensional (3D) data corresponding to the 2D image, the 2D image including a plurality of pixels, the 3D data including a plurality of points; determine, for each of the plurality of pixels in the 2D image, a point in the 3D data corresponding to the pixel in the 2D image; determine a mask image based on the point in the 3D data corresponding to each of the plurality of pixels in the 2D image; determine, based on the mask image, a symmetry related parameter of the face in the 2D image; and correct, based on the symmetry related parameter of the face, the 2D image to generate a corrected 2D image including a front view of the face. ### Claim 18 (depends on 17) The system of claim 17, wherein to determine, for each of the plurality of pixels in the 2D image, the point in the 3D data corresponding to the pixel in the 2D image, the one or more image processing units: determine at least one landmark point in the 2D image; determine at least one point in the 3D data corresponding to the at least one landmark point in the 2D image; determine a projection matrix based on the 3D data and a template 3D model of face; determine a relationship between the 2D image and the 3D data based on the projection matrix; determine, based on the relationship between the 2D image and the 3D data, at least one point in the 3D data corresponding to the at least one landmark point in the 2D image. ### Claim 19 (depends on 17) The system of claim 17, wherein to determine the symmetry related parameter of the face in the 2D image, the one or more image processing units: divide the mask image into a first sub-image and a second sub-image; determine a difference between the first sub-image and the second sub-image; and determine, based on the difference between the first sub-image and the second sub-image, the symmetry related parameter of the face in the 2D image. ### Claim 20 (depends on 17) The system of claim 17, wherein to correct the 2D image, the one or more image processing units: determine a Gaussian image based on the mask image; determine a first coefficient associated with the symmetry related parameter, the mask image, and the Gaussian image; flip the Gaussian image and the 2D image; determine a second coefficient associated with the symmetry related parameter, the mask image, and the flipped Gaussian image; determine a first matrix based on the 2D image and the Gaussian image; determine a second matrix based on the 2D image and the first coefficient; determine a third matrix based on the flipped 2D image and the second coefficient; and correct the 2D image based on the first matrix, the second matrix, and the third matrix. ### Claim at position 21 -28. (canceled)