关键词: 字符分割, 快速提升小波变换, 支持向量机, K-means聚类

Abstract: Complex background including shading, seal and some images has a bad effect on character recognition of check. Thus, in this paper, an effective method that extracts the significant texture characteristics of character from the image by fast lifting wavelet transform was proposed to solve this problem. A coarse-to-fine searching strategy was adopted to distinguish the characters from background at the level of block of pixels and single pixel. First, Support Vector Machine (SVM) was used to classify blocks according to texture characteristics, and during this process text region could be located. Then character segmentation was achieved by using K-means algorithm for clustering the pixels at the text region. The experimental results show the high accuracy and strong robustness of the proposed method at the situation of strong interference of complex texture and seal.

Key words: character segmentation, fast lifting wavelet transform, Support Vector Machine (SVM), K-means clustering