基于Gabor小波变换的汉字识别方法

基于Gabor滤波器时频局域性和方向选择性对应在汉字图像上即是对笔划宽度和方向的选择这一认识，考虑到笔划宽度多峰值、笔划是方向的特点，利用二维Gabor小波的多分辨率特性，对汉字图像进行了多尺度多方向分析，提取多个子平面的滤波器输出系数作为统计特征，实现了字符图像的高性能识别，为开展低质量、低分辨率的汉字字符图像识别研究提供了新方法。实验结果表明，用这种方法识别低分辨率的字符图像，效果优于其他方法。

Gabor wavelet based feature extraction for Chinese character recognition

By using the direction selection ability and frequency locality of Gabor filter, the corresponding relation between the width of stroke of Chinese characters and frequency of the filter is established. Considering the multi-direction of stroke and multi-peak values of stroke width, the two-dimensional Gabor wavelet is used to analyze the Chinese character image in multi-scale and multi-direction. Through drawing the output coefficients of filters as statistic features, the high performance of the character recognition is realized. The experiment results show that the kind of method is superior to other methods, especially on gray or binary character images recognition with low resolution.