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16th International Conference on Pattern Recognition (ICPR'02) - Volume 3   p. 30131
An Evolutionary Approach for the Generation of Diversiform Characters Using a Handwriting Model
Yasuhiro Wada, Nagaoka University of Technology
Hiroyuki Kasuga, Nagaoka University of Technology
Keiichi Sumita, Nagaoka University of Technology

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DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/ICPR.2002.1047812
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Abstract
In pattern recognition, a large number of diversiform characters is necessary to train/test a handwritten character recognition system. However, it is not easy to collect a large number of natural samples. The artificial diversification of characters has been suggested as one means of collecting a variety of characters [1]. In this paper, we show that a handwriting model can be applied to the diversification of characters. The characters diversified by the model can be used as a database of character images for training/testing purposes. Wada amp; Kawato’s handwriting model [2] is based on an optimal principle and the feature space of the characters includes sets of via-points extracted from actual handwritten characters. The handwriting model can be used to generate a variety of characters by changing via-point information . In this paper, we propose a method for generating a large variety of characters by changing via-point information based on a genetic algorithm and we show that the accuracy of a handwritten character recognition system that uses the characters generated by the proposed method as the training data, is equivalent to that of a system composed by using natural data.
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Citation:  Yasuhiro Wada, Hiroyuki Kasuga, Keiichi Sumita, "An Evolutionary Approach for the Generation of Diversiform Characters Using a Handwriting Model," icpr, p. 30131,  16th International Conference on Pattern Recognition (ICPR'02) - Volume 3,  2002