Character segmentation method of check under complex background
YE Long-huan1,WANG Jun-Feng2,GAO Lin3,YUAN Jun1
1. College of Computer Science, Sichuan University, Chengdu Sichuan 610064,China 2. College of Computer Science, Sichuan University, Chengdu Sichuan 610065, China 3. College of Computer Science and Technology, Southwest University of Science and Technology,Mianyang Sichuan 621010,China
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.
叶龙欢 王俊峰 高琳 袁军. 复杂背景下的票据字符分割方法[J]. 计算机应用, 2012, 32(11): 3198-3205.
YE Long-huan WANG Jun-Feng GAO Lin YUAN Jun. Character segmentation method of check under complex background. Journal of Computer Applications, 2012, 32(11): 3198-3205.
LIU H,WU Q,ZHANG H B.Skew detection for complex document images using robust borderlines in both text and non-text regions[J].Pattern Recognitiion Letters,2008,29(13):1893-1900.
[4]
SHIVAKUMARA P, HUANG W, TAN C L.An efficient edge based technique for text detection in video frames[C]// DAS2008:The Eighth IAPR Workshop on Document Analysis Systems. Washington, DC: IEEE Computer Society,2008:307-314.
GLLAVATA J, EWERTH R, FREISLEBEN B. A text detection,localization and segmentation system for OCR in images[C]// ISMSE04:IEEE Sixth International Symposium on Multimedia Software Engineering. Washington, DC: IEEE Computer Society, 2004:310-317.
[11]
SWELDENS W. The lifting scheme: Acustom-design construction of biorthogonal wavelet[J].Applied and Computational Harmonic Analysis,1996;3(2):186-200.
[12]
VAPNIK V N. Statistical learning theory[M].New York: John Wiley,1998.