A Novel Feature Extraction Technique for the Recognition of Segmented Handwritten Characters

Authors:
M. Blumenstein;B. Verma;H. Basli
Affiliations:
-;-;-
Venue:
ICDAR '03 Proceedings of the Seventh International Conference on Document Analysis and Recognition - Volume 1
Year:
2003

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Abstract

High accuracy character recognition techniques canprovide useful information for segmentation-basedhandwritten word recognition systems. This researchdescribes neural network-based techniques for segmentedcharacter recognition that may be applied to thesegmentation and recognition components of an off-linehandwritten word recognition system. Two neuralarchitectures along with two different feature extractiontechniques were investigated. A novel technique forcharacter feature extraction is discussed and comparedwith others in the literature. Recognition results above80% are reported using characters automaticallysegmented from the CEDAR benchmark database as wellas standard CEDAR alphanumerics.