This paper brings a contribution to the problem of efficiently recognizing handwritten words from a limited size lexicon. For that, a multiple classifier system has been developed that analyzes the words from three different approximation levels, in order to get a computational approach inspired on the human reading process. For each approximation level a three-module architecture composed of a zoning mechanism (pseudo-segmenter), a feature extractor and a classifier is defined. The proposed application is the recognition of the Portuguese handwritten names of the months, for which a best recognition rate of 97.7% was obtained, using classifier combination. © 2009 Springer-Verlag Berlin Heidelberg.
CITATION STYLE
De Oliveira, J. J., De Freitas, C. O. A., De Carvalho, J. M., & Sabourin, R. (2009). Handwritten word recognition using multi-view analysis. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5856 LNCS, pp. 371–378). https://doi.org/10.1007/978-3-642-10268-4_44
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