Chinese handwriting identification based on stable spectral feature of texture images

Abstract

In this paper, a spectral feature extraction method based on fast Fourier transformation for writer identification is presented. According to the constructibility of the texture image of handwriting, we put forward an estimation method for mathematical expectation value of texture image's spectral features. This method eliminates the randomness of spectral features and gets stable spectral features. The experiment results show that this approach enhances the identification accuracy to a large extent using data sets with large handwriting samples.