• DocumentCode
    2147977
  • Title

    Stamp Detection in Color Document Images

  • Author

    Micenkova, Barbora ; van Beusekom, J.

  • Author_Institution
    Dept. of Comput. Sci., Aarhus Univ., Aarhus, Denmark
  • fYear
    2011
  • fDate
    18-21 Sept. 2011
  • Firstpage
    1125
  • Lastpage
    1129
  • Abstract
    An automatic system for stamp segmentation and further verification is needed especially for environments like insurance companies where a huge volume of documents is processed daily. However, detection of a general stamp is not a trivial task as it can have different shapes and colors and, moreover, it can be imprinted with a variable quality and rotation. Previous methods were restricted to detection of stamps of particular shapes or colors. The method presented in the paper includes segmentation of the image by color clustering and subsequent classification of candidate solutions by geometrical and color-related features. The approach allows for differentiation of stamps from other color objects in the document such as logos or texts. For the purpose of evaluation, a data set of 400 document images has been collected, annotated and made public. With the proposed method, recall of 83% and precision of 84% have been achieved.
  • Keywords
    computer forensics; document image processing; feature extraction; image colour analysis; image segmentation; pattern clustering; automatic stamp segmentation system; color clustering; color document images; color-related feature; geometrical feature; image segmentation; insurance companies; stamp detection; subsequent classification; Feature extraction; Image color analysis; Image resolution; Image segmentation; Seals; Shape; Vectors; color clustering; computational forensics; image segmentation; stamp detection;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Document Analysis and Recognition (ICDAR), 2011 International Conference on
  • Conference_Location
    Beijing
  • ISSN
    1520-5363
  • Print_ISBN
    978-1-4577-1350-7
  • Electronic_ISBN
    1520-5363
  • Type

    conf

  • DOI
    10.1109/ICDAR.2011.227
  • Filename
    6065485