Text detection in natural images based on character classification

Authors:
Yunxue Shao;Chunheng Wang;Baihua Xiao;Yang Zhang;Linbo Zhang;Long Ma
Affiliations:
Institute of Automation, Chinese Academy of Sciences, Beijing, China;Institute of Automation, Chinese Academy of Sciences, Beijing, China;Institute of Automation, Chinese Academy of Sciences, Beijing, China;Institute of Automation, Chinese Academy of Sciences, Beijing, China;Institute of Automation, Chinese Academy of Sciences, Beijing, China;Institute of Automation, Chinese Academy of Sciences, Beijing, China
Venue:
PCM'10 Proceedings of the Advances in multimedia information processing, and 11th Pacific Rim conference on Multimedia: Part II
Year:
2010

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Abstract

Text information in images is very important for image understanding. In this paper, a text location method based on character classification is proposed. The and-valley image (AVI) and the and-ridge image (ARI) are first extracted from the input image. Then character components are detected from the AVI and ARI respectively, and then these components are sent to a character classifier. Finally,text region can be generated by merging all the recognized components. This approach is robust to font style, font size, font color and the background complexity. It is demonstrated in the experiments that our method is efficient.