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Hierarchical classification in credit card data extraction

  • US 9,213,907 B2
  • Filed: 10/21/2013
  • Issued: 12/15/2015
  • Est. Priority Date: 06/28/2013
  • Status: Active Grant
First Claim
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1. A computer-implemented method to extract card information, comprising:

  • receiving, by one or more computing devices, an image of a card from a camera;

    identifying, by the one or more computing devices, a first area of the image, the first area being selected as a potential location of a digit on the card in the image and of a size that will encompass not more than a single complete digit, the potential location and the size of the first area being identified from a comparison of the image to a database of card layouts stored on the one or more computing devices;

    performing, by the one or more computing devices, a linear classification algorithm on data encompassed by the first area;

    determining, by the one or more computing devices, a confidence level of a first result of the application of the linear classification algorithm to the first area, wherein the confidence level of the first result indicates a likelihood that the first area encompasses the single complete digit;

    determining, by the one or more computing devices, that the first area does not encompasses a single complete digit upon determining that the confidence level of the first result is under a configured threshold;

    identifying, by the one or more computing devices, a second area of the image, the second area being in a different location from the first area and of a size that will encompass not more than a single complete digit;

    performing, by the one or more computing devices, a linear classification algorithm on data encompassed by the second area;

    determining, by the one or more computing devices, a confidence level of a second result of the application of the linear classification algorithm to the second area indicating that the second area encompasses a single complete digit, wherein the confidence level of the second result indicates a likelihood that the second area encompasses the single complete digit;

    determining, by the one or more computing devices, that the second area encompasses the single complete digit upon determining that the confidence level of the second result is over a configured threshold; and

    performing, by the one or more computing devices, an optical character recognition algorithm on the second area upon a determination that the second area encompasses the single complete digit.

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