Text Detection in Images Based on Unsupervised Classification of Edge-based Features
ICDAR '05 Proceedings of the Eighth International Conference on Document Analysis and Recognition
Detecting and reading text in natural scenes
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
Localizing and segmenting text in images and videos
IEEE Transactions on Circuits and Systems for Video Technology
A comprehensive method for multilingual video text detection, localization, and extraction
IEEE Transactions on Circuits and Systems for Video Technology
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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.