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Document authentication using extracted digital fingerprints

  • US 10,043,073 B2
  • Filed: 02/15/2016
  • Issued: 08/07/2018
  • Est. Priority Date: 03/02/2011
  • Status: Active Grant
First Claim
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1. A method comprising:

  • acquiring digital image data of an image of at least a selected authentication region of a document, without printing or adding anything on to the document, and wherein the document has been previously forged or altered at least in the authentication region from its original state;

    extracting at least one native feature from the acquired digital image data from the authentication region, wherein the at least one native feature describes physical characteristics of the authentication region without recognizing content such as alpha-numeric characters that may appear in the authentication region;

    forming a feature vector to represent the at least one native feature in a compact form;

    storing the feature vector in a database record as part of a digital fingerprint of the document in a forgery database for use in detecting forged or altered documents among a class of documents to which the forged or altered document belongs;

    repeating the foregoing steps over additional documents that have been forged or altered to add, respectively, additional feature vectors in additional database records as part of additional digital fingerprints of the additional documents to the forgery database, the additional feature vectors representing corresponding native features in the additional documents;

    acquiring second digital image data of a portion of a suspect document, wherein the portion of the suspect document corresponds to the authentication region used to build the forgery database;

    extracting second features from the second digital image data;

    forming a second feature vector to represent the second features in the compact form;

    querying the forgery database using the second feature vector to obtain a result based on zero or more stored feature vectors that match the second feature vector, each stored feature vector that matches the second feature vector defining a fraud indicator match;

    counting a number of the fraud indicator matches;

    comparing the number of the fraud indicator matches to a predetermined threshold value to determine a confidence level that the suspect document is forged or altered;

    generating a report of the determined confidence level based on the comparison; and

    transmitting the report to a user interface.

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