# US 10,769,489 B2 · Reading test cards using a mobile device > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 10,769,489 B2 - Document ID: US10769489B2 - Status: Granted - Kind: B2 - Application number: 16/435,276 - Filed: 2019-06-07 - Published: 2019-09-26 - Granted: 2020-09-08 - Earliest claimed: 2017-05-22 - Assignees: Bio-Rad Laboratories (Israel) Inc. - Applicants: Bio-Rad Laboratories (Isreal), Inc. - Inventors: Guy Nahum; Nir Broer; Amit Oved; Rivka Monitz - Web page: https://patentgrep.com/patent/US10769489B2 ## CPC - G06V 10/993: {Evaluation of the quality of the acquired pattern} - G06F 18/22: Matching criteria, e.g. proximity measures - G06V 10/242: {by image rotation, e.g. by 90 degrees} - G06V 10/245: {by locating a pattern; Special marks for positioning} - G06V 30/142: using hand-held instruments; Constructional details of the instruments - G06V 10/247: {by affine transforms, e.g. correction due to perspective effects; Quadrilaterals, e.g. trapezoids} - G06V: IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING - G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N) ## Abstract An input image is received from a mobile device. A portion of the input image is determined to correspond to a test card and an image transformation is applied to that portion of the input image. The image transformation rectifies the portion of the input image. Based on the rectified image, a specific test for which the test card includes a result and the result of that test are both identified. ## Claims ### Claim 1 A computing device for interpreting test cards, the device comprising: a template matching subsystem configured to receive an input image from a mobile device and determine that a portion of the input image corresponds to a test card, the test card having a class of a plurality of test card classes, wherein the template matching subsystem is further configured to identify the class of the test card in the input image by comparing potential features in the input image to templates corresponding to each of the plurality of test card classes; an image processing subsystem, operably connected to the template matching subsystem, configured to apply an image transformation to rectify the portion of the input image that corresponds to the test card; a test identification subsystem configured to identify a test type for which the test card includes a test result, where the test type corresponds to a plurality of possible result indicators for tests of the test type, wherein the test type is identified based on the identified test card class and the rectified portion of the input image; and a result identification subsystem configured to determine the test result included on the test card based on the rectified portion of the input image and the possible result indicators corresponding to the identified test type. ### Claim 2 (depends on 1) The computing device of claim 1, wherein determining that the portion of the input image corresponds to the test card comprises: comparing the potential features to a template for a particular test card class to determine a correlation score; and determining that the portion of the input image corresponds to the particular test card class responsive to the correlation score exceeding a threshold. ### Claim 3 (depends on 1) The computing device of claim 1, wherein determining that the portion of the input image corresponds to the test card comprises: comparing the potential features to each of the templates to generate corresponding correlation scores; selecting a first template corresponding to a first class of test card and having a highest correlation score; and determining that the portion of the input image corresponds to a test card of the first class. ### Claim 4 (depends on 1) The computing device of claim 1, wherein the image transformation includes at least one of: cropping the input image, applying a skew correction to the input image, or resizing the input image. ### Claim 5 (depends on 1) The computing device of claim 1, wherein an angle between a focal axis of a camera that captured the input image and the normal to a plane of the test card can be in a range from zero degrees to forty-five degrees without substantially impacting a reliability of the identified result. ### Claim 6 (depends on 1) The computing device of claim 1, wherein a distance between a camera that captured the input image and the test card can be in a range from five centimeters to thirty centimeters without substantially impacting a reliability of the identified result. ### Claim 7 (depends on 1) The computing device of claim 1, wherein the input image is captured by a camera of the mobile device, the test card is physically separate from the camera at a time the image is captured, and the test card is not supported by an attachment connected to the mobile device. ### Claim 8 (depends on 1) The computing device of claim 1, wherein the test identification subsystem identifies the test type by providing at least a portion of the rectified image to a support vector machine, the support vector machine having been trained to identify the test type from among a plurality of possible test types. ### Claim 9 (depends on 1) The computing device of claim 1, wherein the result identification subsystem determines the test result by providing at least a portion of the rectified image and the plurality of possible result indicators of the test type to a support vector machine, the support vector machine having been trained to identify the test result from among a plurality of possible results. ### Claim 10 A method comprising: receiving an input image from a mobile device; determining that a portion of the input image corresponds to a test card, the test card having a class of a plurality of test card classes; identifying the class of the test card in the input image by comparing potential features in the input image to templates corresponding to each of the plurality of test card classes; applying an image transformation to rectify the portion of the input image that corresponds to the test card; identifying a test type for which the test card includes a test result, where the test type corresponds to a plurality of possible result indicators for tests of the test type, wherein the test type is identified based on the identified test card class and the rectified portion of the input image; and determining the test result included on the test card based on the rectified portion of the input image and the possible result indicators corresponding to the identified test type. ### Claim 11 (depends on 10) The method of claim 10, wherein determining that the portion of the input image corresponds to the test card comprises: comparing the potential features to a template for a particular test card class to determine a correlation score; and determining that the portion of the input image corresponds to the particular test card class responsive to the correlation score exceeding a threshold. ### Claim 12 (depends on 10) The method of claim 10, wherein determining that the portion of the input image corresponds to the test card comprises: comparing of potential features to each of the templates to generate corresponding correlation scores; selecting a first template corresponding to a first class of test card and having a highest correlation score; and determining that the portion of the input image corresponds to a test card of the first class. ### Claim 13 (depends on 10) The method of claim 10, wherein the image transformation includes at least one of: cropping the input image, applying a skew correction to the input image, or resizing the input image. ### Claim 14 (depends on 10) The method of claim 10, wherein an angle between a focal axis of a camera that captured the input image and the normal to a plane of the test card can be in a range from zero degrees to forty-five degrees without substantially impacting a reliability of the identified result. ### Claim 15 (depends on 10) The method of claim 10, wherein a distance between a camera that captured the input image and the test card can be in a range from five centimeters to thirty centimeters without substantially impacting a reliability of the identified result. ### Claim 16 (depends on 10) The method of claim 10, wherein the input image is captured by a camera of the mobile device, the test card is physically separate from the camera at a time the image is captured, and the test card is not supported by an attachment connected to the mobile device. ### Claim 17 (depends on 10) The method of claim 10, wherein identifying the test type comprises providing at least a portion of the rectified image to a support vector machine, the support vector machine having been trained to identify the specific test from among a plurality of possible tests. ### Claim 18 (depends on 10) The method of claim 10, wherein identifying the test result comprises providing at least a portion of the rectified image and the plurality of possible result indicators of the test type to a support vector machine, the support vector machine having been trained to identify the test result from among a plurality of possible results. ### Claim 19 A system comprising: a mobile device having a camera and a display, the camera configured to obtain an image including a test card, the test card having a class of a plurality of test card classes, wherein the template matching subsystem is further configured to identify the class of the test card in the input image by comparing potential features in the input image to templates corresponding to each of the plurality of test card classes, the test card being physically separate from the camera at a time the image is captured and not supported by an attachment connected to the mobile device, and the display configured to display the test result determined from the image; and a diagnostic server, communicably coupled to the mobile device, and configured to: receive the image from the mobile device; apply an image transformation to the image, the image transformation rectifying the image; determine a test type for which the test card includes a test result, where the test type corresponds to a plurality of possible result indicators for tests of the test type, wherein the test type is identified based on the identified test card class and the rectified image; determine the test result included on the test card based on the rectified image and the possible result indicators corresponding to the identified test type; and send the result to the mobile device. ### Claim 20 (depends on 19) The system of claim 19, wherein the diagnostic server determines the test result by using a support vector machine to identify a test type and identify the result from a plurality of possible results for the test type. ### Claim 21 A non-transitory computer-readable storage medium storing instructions that, when executed by a computing device, cause the computing device to perform operations comprising: receiving an input image from a mobile device; determining that a portion of the input image corresponds to a test card, the test card having a class of a plurality of test card classes, wherein the template matching subsystem is further configured to identify the class of the test card in the input image by comparing potential features in the input image to templates corresponding to each of the plurality of test card classes; applying an image transformation to rectify the portion of the input image that corresponds to the test card; identifying a test type for which the test card includes a test result, where the test type corresponds to a plurality of possible result indicators for tests of the test type, wherein the test type is identified based on the identified test card class and the rectified portion of the input image; and determining the test result included on the test card based on the rectified portion of the input image and the possible result indicators corresponding to the identified test type. ### Claim 22 (depends on 21) The non-transitory computer-readable storage medium of claim 21, wherein determining that the portion of the input image corresponds to the test card comprises: comparing the potential features to a template for a particular test card class to determine a correlation score; and determining that the portion of the input image corresponds to the particular test card class responsive to the correlation score exceeding a threshold. ### Claim 23 (depends on 21) The non-transitory computer-readable storage medium of claim 21, wherein determining that the portion of the input image corresponds to the test card comprises: comparing of potential features to each of the templates to generate corresponding correlation scores; selecting a first template corresponding to a first class of test card and having a highest correlation score; and determining that the portion of the input image corresponds to a test card of the first class. ### Claim 24 (depends on 21) The non-transitory computer-readable storage medium of claim 21, wherein the image transformation includes at least one of: cropping the input image, applying a skew correction to the input image, or resizing the input image. ### Claim 25 (depends on 21) The non-transitory computer-readable storage medium of claim 21, wherein an angle between a focal axis of a camera that captured the input image and the normal to a plane of the test card can be in a range from zero degrees to forty-five degrees without substantially impacting a reliability of the identified result. ### Claim 26 (depends on 21) The non-transitory computer-readable storage medium of claim 21, wherein a distance between a camera that captured the input image and the test card can be in a range from five centimeters to thirty centimeters without substantially impacting a reliability of the identified result. ### Claim 27 (depends on 21) The non-transitory computer-readable storage medium of claim 21, wherein the input image is captured by a camera of the mobile device, the test card is physically separate from the camera at a time the image is captured, and the test card is not supported by an attachment connected to the mobile device. ### Claim 28 (depends on 21) The non-transitory computer-readable storage medium of claim 21, wherein identifying the test type comprises providing at least a portion of the rectified image to a support vector machine, the support vector machine having been trained to identify the specific test from among a plurality of possible tests. ### Claim 29 (depends on 21) The non-transitory computer-readable storage medium of claim 21, wherein identifying the test result comprises providing at least a portion of the rectified image and the plurality of possible result indicators of the test type to a support vector machine, the support vector machine having been trained to identify the test result from among a plurality of possible results.