Abstract
This paper describes a new feature extraction method contributing to improvement of the performance of a handwritten Chinese character recognition system. By using enhanced weighted dynamic meshes based on nonlinear normalization, this method not only avoids the zigzags and other undesirable side effects introduced in the original Yamada et al.’s nonlinear normalization method but also avoids additional feature normalization process in the original Lian-Wen Jin et al.’s and WU Tian-lei et al.’s dynamic mesh method. Experiment on HCL2000, a handwritten Chinese character database, shows that our method achieves superior performance.
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© 2005 Springer-Verlag Berlin Heidelberg
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Chen, G., Zhang, HG., Guo, J. (2005). Feature Extraction for Handwritten Chinese Character by Weighted Dynamic Mesh Based on Nonlinear Normalization. In: Singh, S., Singh, M., Apte, C., Perner, P. (eds) Pattern Recognition and Data Mining. ICAPR 2005. Lecture Notes in Computer Science, vol 3686. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11551188_62
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DOI: https://doi.org/10.1007/11551188_62
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-28757-5
Online ISBN: 978-3-540-28758-2
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