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.

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.

Abstract: A computer implemented method for correcting distortion in an image of a page includes identifying a set of high quality (HQ) words in undistorted regions of one or more images of pages having content related to the content of the page. At least one distorted word in the image the page is identified such that each distorted word corresponds to a high quality word of the set. A global transformation function is generated for application to the image of the page so as to transform the distorted word into its corresponding high quality word. The global transformation function is applied to pixels of the image of the page.

Abstract: A method, including calculating a first distance matrix for a first binary image and a second distance matrix for a second binary image, and calculating a first gradient matrix for the first distance matrix and a second gradient matrix for the second distance matrix. Using the calculated distance and gradient matrices, a displacement matrix is calculated that defines a change in position between elements in the first distance matrix and corresponding elements in the second distance matrix. Outlier elements are identified including elements in the displacement matrix satisfying at least one predetermined criterion, and the identified outlier are replaced with calculated interpolated values.

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.

Abstract: A computer implemented method for adaptive optical character recognition on a document with distorted characters includes performing a distortion-correction transformation on a segmented character of the document assuming the segmented character to be a candidate character. The method further includes comparing the transformed segmented character to the candidate character by calculating a comparison score. If the calculated score is within a predetermined range, the segmented character is identified with the candidate character. The method may be implemented in either of computer hardware configured to perform the method, or in computer software embodied in a non-transitory, tangible, computer-readable storage medium. Also disclosed are corresponding computer program product and data processing system.

Abstract: A method, including calculating a first distance matrix for a first binary image and a second distance matrix for a second binary image, and calculating a first gradient matrix for the first distance matrix and a second gradient matrix for the second distance matrix. Using the calculated distance and gradient matrices, a displacement matrix is calculated that defines a change in position between elements in the first distance matrix and corresponding elements in the second distance matrix. Outlier elements are identified including elements in the displacement matrix satisfying at least one predetermined criterion, and the identified outlier are replaced with calculated interpolated values.

Abstract: A computer implemented method for adaptive optical character recognition on a document with distorted characters includes performing a distortion-correction transformation on a segmented character of the document assuming the segmented character to be a candidate character. The method further includes comparing the transformed segmented character to the candidate character by calculating a comparison score. If the calculated score is within a predetermined range, the segmented character is identified with the candidate character. The method may be implemented in either of computer hardware configured to perform the method, or in computer software embodied in a non-transitory, tangible, computer-readable storage medium. Also disclosed are corresponding computer program product and data processing system.

Abstract: A computer implemented method for correcting distortion in an image of a page includes identifying a set of high quality (HQ) words in undistorted regions of one or more images of pages having content related to the content of the page. At least one distorted word in the image the page is identified such that each distorted word corresponds to a high quality word of the set. A global transformation function is generated for application to the image of the page so as to tranform the distorted word into its corresponding high quality word. The global transformation function is applied to pixels of the image of the page.