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. © 2012 Springer-Verlag Berlin Heidelberg.
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CITATION STYLE
Czúni, L., Szöke, T., & Gál, M. (2012). Recognition of hand-written archive text documents. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7594 LNCS, pp. 337–344). Springer Verlag. https://doi.org/10.1007/978-3-642-33564-8_41
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