# US 2013/0294697 A1 · Systems and methods for processing mobile images to identify and extract content from forms > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 2013/0294697 A1 - Document ID: US20130294697A1 - Status: Published application - Kind: A1 - Application number: 13/844,511 - Filed: 2013-03-15 - Published: 2013-11-07 - Earliest claimed: 2008-01-18 - Assignees: Mitek Systems, Inc. - Applicants: Mitek Systems - Inventors: Grigori Nepomniachtchi; Vitali Kliatskine; Vladimir Kluzner - Web page: https://patentgrep.com/patent/US20130294697A1 ## CPC - G06Q 20/042: {characterized in that the payment protocol involves at least one cheque} - G06F 18/22: Matching criteria, e.g. proximity measures - G06Q 20/10: specially adapted for electronic funds transfer [EFT] systems; specially adapted for home banking systems - G06Q 20/3276: {using a pictured code, e.g. barcode or QR-code, being read by the M-device} - G06V 10/32: Normalisation of the pattern dimensions - G06V 30/412: Layout analysis of documents structured with printed lines or input boxes, e.g. business forms or tables - H04N 1/00244: {with a server, e.g. an internet server (fax-servers or the like for store and forward H04N1/324)} - H04N 1/00307: {with a mobile telephone apparatus (constructional features of portable telephone sets H04M1/0202; mobile radio systems H04W84/00)} - H04N 2101/00: Still video cameras - H04N 2201/001: Sharing resources, e.g. processing power or memory, with a connected apparatus or enhancing the capability of the still picture apparatus - H04N 2201/0084: Digital still camera - G06Q: INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR - 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 Systems and methods for matching a received image with a template image are disclosed herein. Such systems and methods can advantageously enable an image captured by a mobile device (such as a smartphone or digital camera) to be correctly identified by the processing application. In some embodiments, the received image is first resized in one or both dimensions in order to match or approximately match the dimensions of a given template. The received image and template image can then be superimposed. Next, an optimal translative transformation value can be calculated in order to generate a confidence level for the current possible match. After confidence levels for each template are generated and recorded, the template with the highest confidence level can be selected as the best match for the received image. ## Claims ### Claim 1 A computer readable medium containing instructions which, when executed by a computer, perform a process of resizing a dimension of a received image to match or approximately match a corresponding dimension of template image, the process comprising: identifying a first set of lines in a received image and a second set of lines in a template image; selecting a first subset of lines from the first set of lines, and selecting a second subset of lines from the second set of lines, wherein each line of the first subset is longer than a first predetermined minimum length, and wherein each line of the subset is longer than a second predetermined minimum length; calculating distances between subsequent lines in the first subset, and calculating distances between subsequent lines in the second subset; calculating ratios between successive distances in the first subset, and calculating ratios between subsequent distances in the second subset; pairing ratios in the first subset with ratios in the second subset if the differences between two ratios exceeds a predetermined threshold of similarity; for each matching pair of ratios, calculating a ratio similarity coefficient that is less than or equal to a predetermined value; storing each ratio similarity coefficient in a similarity coefficient vector; sorting the vector; calculating a hypothesis similarity coefficient based at least in part upon the median of the sorted vector; from a set of all hypothesis similarity coefficients calculated in this manner, selecting the hypothesis similarity coefficient with the greatest value; and resizing the dimension of the received image based at least in part upon the selected hypothesis similarity coefficient. ### Claim 2 (depends on 1) The computer readable medium of claim 1, wherein the first and second sets of lines consist of horizontal lines. ### Claim 3 (depends on 1) The computer readable medium of claim 1, wherein the first and second sets of lines consist of vertical lines. ### Claim 4 (depends on 1) The computer readable medium of claim 1, wherein the first predetermined minimum length is 70% of the length of the longest line of the first set of lines. ### Claim 5 (depends on 1) The computer readable medium of claim 1, wherein the second predetermined minimum length is 70% of the length of the longest line of the second set of lines. ### Claim 6 (depends on 1) The computer readable medium of claim 1, wherein a ratio of the first subset may only be paired to a single ratio of the second subset. ### Claim 7 (depends on 1) The computer readable medium of claim 1, wherein no more than a single ratio of the first subset may be paired to a ratio of the second subset. ### Claim 8 (depends on 1) The computer readable medium of claim 1, wherein the predetermined value is equal to 1.0. ### Claim 9 (depends on 1) The computer readable medium of claim 1, wherein the process is repeated a second time, but while reversing the sequence of lines contained within the first subset in order to account for vertical inversion of the received image. ### Claim 10 (depends on 1) The computer readable medium of claim 1, wherein resizing the dimension of the received image is based at least in part upon a determined ratio, the determined ratio comprising a coordinate difference between a first and last line of the received image, and a coordinate difference between a first and last line of the template image. ### Claim 11 (depends on 1) The computer readable medium of claim 1, wherein the dimension is the height of the received image. ### Claim 12 (depends on 1) The computer readable medium of claim 1, wherein the dimension is the width of the received image. ### Claim 13 A computer readable medium containing instructions which, when executed by a computer, perform a process of calculating an optimal translation transformation, the process comprising: identifying data items within a received image and within a template image; inflating the pixels of one or more of the data items according to their respective aspect ratios; creating a bounding rectangle for each inflated item; for each corresponding pair of data items, calculating the difference between the geometric centers of each respective bounding rectangle; creating a weighted sum of translation transformations, wherein the weighted sum comprises the values of each calculated difference; and determining a registration confidence level based at least in part upon the weighted sum. ### Claim 14 (depends on 13) The computer readable medium of claim 13, wherein the data items comprise horizontal lines, vertical lines, text, and boxes. ### Claim 15 (depends on 14) The computer readable medium of claim 14, wherein the boxes are identified based at least in part upon previously detected horizontal and vertical lines. ### Claim 15 (depends on 14) The computer readable medium of claim 14, wherein if the data item is a horizontal line or text, inflating the pixels comprises inflating the data item for a number of pixels in a vertical direction. ### Claim 16 (depends on 14) The computer readable medium of claim 14, wherein if the data item is a vertical line, inflating the pixels comprises inflating the data item for a number of pixels in a horizontal direction. ### Claim 17 (depends on 14) The computer readable medium of claim 14, wherein if the data item is a box, inflating the pixels comprises inflating the data item for a number of pixels in a both a horizontal and a vertical direction. ### Claim 18 (depends on 14) The computer readable medium of claim 14, wherein determining the registration confidence level is determined based at least in part upon calculating a weighted sum of cross-correlation coefficients. ### Claim 19 A computer readable medium containing instructions which, when executed by a computer, performs a process of matching a received image to a corresponding template image, the process comprising: receiving an image; for a set of template images remaining: resizing one or both dimensions of the received image to match or approximately match a corresponding dimension of the current template image, calculating the optimal translation transformation of the received image relative to the current template image, recording a calculated confidence level that is based at least in part on the optimal translation transformation; and selecting the template image which has the highest confidence level. ### Claim 20 (depends on 19) The computer readable medium of claim 19, wherein resizing one or both dimensions of the received image to match or approximately match a corresponding dimension of the current template image further comprises: identifying a first set of lines in the received image and a second set of lines in the template image; selecting a first subset of lines from the first set of lines, and selecting a second subset of lines from the second set of lines, wherein each line of the first subset is longer than a first predetermined minimum length, and wherein each line of the subset is longer than a second predetermined minimum length; calculating distances between subsequent lines in the first subset, and calculating distances between subsequent lines in the second subset; calculating ratios between successive distances in the first subset, and calculating ratios between subsequent distances in the second subset; pairing ratios in the first subset with ratios in the second subset if the differences between two ratios exceeds a predetermined threshold of similarity; for each matching pair of ratios, calculating a ratio similarity coefficient that is less than or equal to a predetermined value; storing each ratio similarity coefficient in a similarity coefficient vector; sorting the vector; calculating a hypothesis similarity coefficient based at least in part upon the median of the sorted vector; from a set of all hypothesis similarity coefficients calculated in this manner, selecting the hypothesis similarity coefficient with the greatest value; and resizing a dimension of the received image based at least in part upon the selected hypothesis similarity coefficient. ### Claim 21 (depends on 19) The computer readable medium of claim 19, wherein calculating the optimal translation transformation of the received image relative to the current template image further comprises: identifying data items within the received image and within the template image; inflating the pixels of one or more of the data items according to their respective aspect ratios; creating a bounding rectangle for each inflated item; for each corresponding pair of data items, calculating the difference between the geometric centers of each respective bounding rectangle; creating a weighted sum of translation transformations, wherein the weighted sum comprises the values of each calculated difference; and determining a registration confidence level based at least in part upon the weighted sum.