关键词: 脱机手写体汉字, 模糊支持向量机, 像素密度, 小波

Abstract: Considering the features of off-line handwritten Chinese characters, this paper presents a course classification method based on FSVM（Fuzzy Support Vector Machine）. According to pixel density characteristics of wavelet decomposition, writer makes coarse classification on Chinese characters by using FSVM. On extracting peripheral features through fine classification and recognition, together with wavelet multi-grid characteristics, this paper relatively succeeds to do fine recognition by one-against-all method. The emulation test shows that the new method has a high recognition rate.

Key words: off-line handwritten Chinese characters, Fuzzy Support Vector Machine（FSVM）, pixel density, wavelet