关键词: 维吾尔文, 签名识别, 方向特征, 局部中心点特征, K-NN分类器

Abstract: In this paper, on the basis of preprocessing procedures such as binarization, noise removing, normalization and thinning, each Uyghur handwritten signature image is segmented into several sub images with Pyramid resolution to combined with the structure and writing style of the signature, the 16-dementional directional features are extracted in higher resolution layer, while 32-dementional local central point features are extracted in the lower resolution layer. 95.5% and 90.5% of recognition rates are obtained using the two features. In order to further improve the recognition rate, the two features are combined together, and then the recognition rate is increased up to 98.5%. The effectiveness of Euclidean distance and Chi-square distance based measurement methods to the recognition rates are also analyzed, and it is confirmed that Chi-square distance is the best measurement method in this paper.

Key words: Uyghur, signature recognition, directional feature, central point local feature, K-NN classfier