Abstract
In this paper, we focus on the text extraction of image, and propose a new approach for it into two phases: Firstly, for the effective binarization of text region image, instead of performing the binarization in a constant color plane as in the existing methods, our approach adaptively selects the relatively best color plane for the binarization, which uses the text contrast difference among the color planes. Secondly, to remove the noise in the binary image, we consider the color difference between the text strokes and noises, and the colorbased clustering is then utilized to remove the noise for the effective text recognition. The experimental result has shown that the proposed approach is better than the existing methods in terms of the performance of text extraction. © Springer-Verlag Berlin Heidelberg 2007.
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Yi, J., Peng, Y., & Xiao, J. (2007). Color-based text extraction for the image. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4810 LNCS, pp. 393–396). Springer Verlag. https://doi.org/10.1007/978-3-540-77255-2_43
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