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A Novel Multi-oriented Chinese Text Extraction Approach from Videos

Video texts contain useful high level information which contributes to video indexing and retrieval. This paper proposed a novel video text extraction method for Chinese text of any orientation. Firstly, candidate text regions are detected by a wavelet based algorithm. Secondly, horizontal, vertical, slant, curve or arc text lines are merged by color and space relationship based on arrangement structures of multi-oriented text lines in these candidate regions. And then character segmentation will automatically choose best fit strategies based on structure analysis, due to the complex structures (single, up-down, left-right, encircling) of Chinese characters. Finally, a SVM classifier eliminates false positives. The experimental results show the proposed approach is robust for Chinese texts of any orientation in videos.