Handwritten Word Recognition Using Multi-view Analysis

Authors:
J. J. Oliveira, Jr.;C. O. A. Freitas;J. M. Carvalho;R. Sabourin
Affiliations:
UFRN - Universidade Federal do Rio Grande do Norte,;PUC-PR - Pontíficia Universidade Católica do Paraná,;UFCG - Universidade Federal de Campina Grande,;ÉTS - École de Technologie Supérieure,
Venue:
CIARP '09 Proceedings of the 14th Iberoamerican Conference on Pattern Recognition: Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications
Year:
2009

Citing 3
Cited 0

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Handwritten Isolated Word Recognition: An Approach Based on Mutual Information for Feature Set Validation

ICDAR '01 Proceedings of the Sixth International Conference on Document Analysis and Recognition

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Abstract

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.