• DocumentCode
    3485671
  • Title

    A System Based on Intrinsic Features for Fraudulent Document Detection

  • Author

    Bertrand, Romain ; Gomez-Kramer, Petra ; Ramos Terrades, Oriol ; Franco, Paulo ; Ogier, Jean-Marc

  • Author_Institution
    Lab. L3i, Univ. of La Rochelle, La Rochelle, France
  • fYear
    2013
  • fDate
    25-28 Aug. 2013
  • Firstpage
    106
  • Lastpage
    110
  • Abstract
    Paper documents still represent a large amount of information supports used nowadays and may contain critical data. Even though official documents are secured with techniques such as printed patterns or artwork, paper documents suffer from a lack of security. However, the high availability of cheap scanning and printing hardware allows non-experts to easily create fake documents. As the use of a watermarking system added during the document production step is hardly possible, solutions have to be proposed to distinguish a genuine document from a forged one. In this paper, we present an automatic forgery detection method based on document´s intrinsic features at character level. This method is based on the one hand on outlier character detection in a discriminant feature space and on the other hand on the detection of strictly similar characters. Therefore, a feature set is computed for all characters. Then, based on a distance between characters of the same class, the character is classified as a genuine one or a fake one.
  • Keywords
    document image processing; feature extraction; image classification; object detection; automatic forgery detection method; character classification; document intrinsic features; document production step; feature set; fraudulent document detection; information supports; intrinsic features; paper documents; watermarking system; Feature extraction; Forgery; Noise; Security; Shape; Software; Vectors; document analysis; fake; forgery; fraudulent document; paper document;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Document Analysis and Recognition (ICDAR), 2013 12th International Conference on
  • Conference_Location
    Washington, DC
  • ISSN
    1520-5363
  • Type

    conf

  • DOI
    10.1109/ICDAR.2013.29
  • Filename
    6628594