Handwritten Chinese Character Recognition: Alternatives to Nonlinear Normalization
ICDAR '03 Proceedings of the Seventh International Conference on Document Analysis and Recognition - Volume 1
Normalization-Cooperated Gradient Feature Extraction for Handwritten Character Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Recognition of handwritten Chinese characters by critical region analysis
Pattern Recognition
Handwritten Chinese character recognition: effects of shape normalization and feature extraction
SACH'06 Proceedings of the 2006 conference on Arabic and Chinese handwriting recognition
International Journal of Applied Mathematics and Computer Science
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A part of the authors have been proposed a few nonlinear normalization methods using line density for handwritten characters and it was verified that those nonlinear methods were more effective than a linear method. Those nonlinear methods, however, could not use two-dimensional information of the line density, because the line density was projected on to the axes of coordinates. This paper proposes an extended nonlinear normalization method which uses two-dimensional information of the line density. It is confirmed that the proposed method is more powerful than conventional methods by experiments tested on the handwritten character database ETL-8.