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.
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Shao, Y., Wang, C., Xiao, B., Zhang, Y., Zhang, L., Ma, L. (2010). Text Detection in Natural Images Based on Character Classification. In: Qiu, G., Lam, K.M., Kiya, H., Xue, XY., Kuo, CC.J., Lew, M.S. (eds) Advances in Multimedia Information Processing - PCM 2010. PCM 2010. Lecture Notes in Computer Science, vol 6298. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15696-0_68
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DOI: https://doi.org/10.1007/978-3-642-15696-0_68
Publisher Name: Springer, Berlin, Heidelberg
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