Correcting bound document images based on automatic and robust curved text lines estimation

Authors:
Yichao Ma;Chunheng Wang;Ruwei Dai
Affiliations:
Laboratory of Complex System and Intelligent Science, Institute of Automation, Chinese Academy of Science, Beijing, P.R. China;Laboratory of Complex System and Intelligent Science, Institute of Automation, Chinese Academy of Science, Beijing, P.R. China;Laboratory of Complex System and Intelligent Science, Institute of Automation, Chinese Academy of Science, Beijing, P.R. China
Venue:
ICCPOL'06 Proceedings of the 21st international conference on Computer Processing of Oriental Languages: beyond the orient: the research challenges ahead
Year:
2006

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Abstract

Geometric distortion often occurs when taking images of bound documents. This phenomenon greatly impairs recognition accuracy. In this paper, a new one-image based method is proposed to correct geometric distortion in bound document images. According to this method, the document image is binarized first. Next, curved text-line features are extracted. Thirdly, locally optimized text curves are detected using a graph model. Finally, the technique of texture warping is applied to correct the image. Experimental results show that images restored by our proposed method can achieve good perception and recognition results.