关键词: 手写体维文字符, Gabor滤波器, 方向线素, K最近邻（KNN）识别分类器

Abstract: This paper gives a recognition algorithm which combines 2 features of the hand-written Uyghur character. The algorithm extracts the real value Gabor energy feature and directional element feature of hand-written Uyghur character, combining the 128 dimension real value Gabor energy feature and the 128 dimension directional element feature together, uses KNN classifier to unitedly classify these two features. It recognizes the character feature and the handwriting feature for the samples in the database of the hand-written Uyghur character. The experimental result shows, the algorithm is more remarkable in recognition of the handwritten Uyghur character than using one feature. The algorithm can also be used in recognition of handwritten Arabic character.

Key words:  hand-written Uyghur character, Gabor filter, directional element, K-Nearest Neighbor（KNN） recognition classifier