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Rejection Strategies with Multiple Classifiers for Handwritten Character Recognition

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5 Author(s)
Xu-Cheng Yin ; Dept. of Comput. Sci., Univ. of Sci. & Technol., Beijing, China ; Hong-Wei Hao ; Yun-Feng Tang ; Jun Sun
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With rejection strategies in a handwriting recognition system, we are able to improve the reliability and accuracy of the recognized characters. In this paper, we propose several rejection strategies with multiple classifiers for handwritten character recognition. First, the rejection strategy for the single classifier is introduced, which is composed of three stages: initial scaling, confidence measure calculation, and rejection performing. Then, we analyze rejection strategies for multiple classifiers. We divided our rejection strategies into two categories: (1) for voting combination; and (2) for linear combination with multiple classifiers. In the voting combination style, three rejection strategies, OR, AND, and VOTING, are proposed. And for the linear combination one, rejection strategies for average and weighted combination are analyzed respectively. We also experiment and compare our rejection strategies with handwritten digit recognition.

Published in:

Document Analysis and Recognition, 2009. ICDAR '09. 10th International Conference on

Date of Conference:

26-29 July 2009

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