Similar pattern discrimination by filter mask learning with probabilistic descent

Authors:
Yoshiaki Kurosawa
Affiliations:
Toshiba Solutions Co., Advanced Technology Development, Platform Solutions Div., Fuchu-shi, Tokyo, Japan
Venue:
SCIA'07 Proceedings of the 15th Scandinavian conference on Image analysis
Year:
2007

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Abstract

The purpose of this research was to examine the learning system for a feature extraction unit in OCR. Average Risk Criterion and Probabilistic Descent (basic model of MCE/GPD) are employed in the character recognition system which consists of feature extraction with filters and Euclidian distance. The learning process was applied to the similar character discrimination problem and the effects were shown as the accuracy improvement.