Robust Stamps Detection and Classification by Means of General Shape Analysis

  • Paweł Forczmański
  • Dariusz Frejlichowski
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6374)


The article presents current challenges in stamp detection problem. It is a crucial topic these days since more and more traditional paper documents are being scanned in order to be archived, sent through the net or just printed. Moreover, an electronic version of paper document stored on a hard drive can be taken as forensic evidence of possible crime. The main purpose of the method presented in the paper is to detect, localize and segment stamps (imprints) from the scanned document. The problem is not trivial since there is no such thing like ”stamp standard”. There are many variations in size, shape, complexity and ink color. It should be remembered that the scanned document may be degraded in quality and the stamp can be placed on relatively complicated background. The algorithm consists of several steps: color segmentation and pixel classification, regular shapes detection, candidates segmentation and verification. The paper includes also the initial results of selected experiments on real documents having different types of stamps.


Document Image Color Segmentation Forensic Evidence Color Separation Real Document 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Paweł Forczmański
    • 1
  • Dariusz Frejlichowski
    • 1
  1. 1.Faculty of Computer Science and Information TechnologyWest Pomeranian University of Technology, SzczecinSzczecinPoland

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