Recognition of Hand-Written Archive Text Documents

  • László Czúni
  • Tamás Szöke
  • Mónika Gál
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7594)


The processing of the large amount of hand-written archive documents is an unsolved problem. We propose a semi-automatic text recognition approach for those documents containing a limited size of vocabulary. Our approach is word based and uses the Scale Invariant Feature Transform for finding and describing saliency points of hand-written words. For testing we used a book of a Central-European city census of the year 1771 containing mainly Christian and family names. At reasonable database size we could achieve about 80% recognition rate.


Optical character recognition Hand-written text recognition Feature extraction SIFT Archive document processing 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • László Czúni
    • 1
  • Tamás Szöke
    • 1
  • Mónika Gál
    • 2
  1. 1.Department of Electrical Engineering and Information SystemsUniversity of PannoniaVeszprémHungary
  2. 2.Department of MathematicsUniversity of PannoniaVeszprémHungary

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