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Recognition of Hand-Written Archive Text Documents

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Computer Vision and Graphics (ICCVG 2012)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 7594))

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Abstract

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.

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Author information

Authors and Affiliations

  1. Department of Electrical Engineering and Information Systems, University of Pannonia, Egyetem utca 10, Veszprém, H-8200, Hungary

    László Czúni & Tamás Szöke

  2. Department of Mathematics, University of Pannonia, Egyetem utca 10, Veszprém, H-8200, Hungary

    Mónika Gál

Authors
  1. László Czúni
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  2. Tamás Szöke
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  3. Mónika Gál
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Editor information

Editors and Affiliations

  1. Polish-Japanese Institute of Information Technology, 86 Koszykowa, 02-008, Warsaw, Poland

    Leonard Bolc

  2. AGH University of Science and Technology, Mickiewicza 30, 30-059, Kraków, Poland

    Ryszard Tadeusiewicz

  3. Faculty of Applied Informatics and Mathematics, Department of Informatics, Warsaw University of Life Sciences (SGGW), Nowoursynowska 159, 02-776, Warsaw, Poland

    Leszek J. Chmielewski

  4. Polish-Japanese Institute of Information Technology, Koszykowa 86, 02-008, Warszawa, Poland

    Konrad Wojciechowski

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© 2012 Springer-Verlag Berlin Heidelberg

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Czúni, L., Szöke, T., Gál, M. (2012). Recognition of Hand-Written Archive Text Documents. In: Bolc, L., Tadeusiewicz, R., Chmielewski, L.J., Wojciechowski, K. (eds) Computer Vision and Graphics. ICCVG 2012. Lecture Notes in Computer Science, vol 7594. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33564-8_41

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  • DOI: https://doi.org/10.1007/978-3-642-33564-8_41

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-33563-1

  • Online ISBN: 978-3-642-33564-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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