A weighted competitive learning method extracting skeleton pattern from Japanese Kanji characters

A weighted competitive learning (WCL) method was proposed by authors for extracting skeleton patterns from digit and alphabet characters. The extracted pattern is essential in character recognition. It can satisfy the following important requirements. (a) Insensitive to irregular edge lines. (b) Nonstructure patterns are not extracted. (c) Insensitive to nonuniform line width. (d) Line information should be held even though the line width widely changes in a character. In this paper, the previous WCL method is improved for application to more complicated characters, such as Japanese Kanji characters. Furthermore, a PDP model, implements the WCL method, is provided.<
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