Recognition of hand-written archive text documents

Authors:
László Czúni;Tamás Szöke;Mónika Gál
Affiliations:
Department of Electrical Engineering and Information Systems, University of Pannonia, Veszprém, Hungary;Department of Electrical Engineering and Information Systems, University of Pannonia, Veszprém, Hungary;Department of Mathematics, University of Pannonia, Veszprém, Hungary
Venue:
ICCVG'12 Proceedings of the 2012 international conference on Computer Vision and Graphics
Year:
2012

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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.