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	Multi-polarity text segmentation using graph theory
	Li, Jia ; Tian, Yonghong ; Huang, Tiejun ; Gao, Wen
	2008
英文摘要	Text segmentation, or named text binarization, is usually an essential step for text information extraction from images and videos. However, most existing text segmentation methods have difficulties in extracting multi-polarity texts, where multi-polarity texts mean those texts with multiple colors or intensities in the same line. In this paper, we propose a novel algorithm for multi-polarity text segmentation based on graph theory. By representing a text image with an undirected weighted graph and partitioning it iteratively, multi-polarity text image can be effectively split into several single-polarity text images. As a result, these text images are then segmented by single-polarity text segmentation algorithms. Experiments on thousands of multi-polarity text images show that our algorithm can effectively segment multi-polarity texts. ? 2008 IEEE.; EI; 0
语种	英语
DOI标识	10.1109/ICIP.2008.4712428
内容类型	其他
源URL	[http://ir.pku.edu.cn/handle/20.500.11897/327608]
专题	信息科学技术学院
推荐引用方式 GB/T 7714	Li, Jia,Tian, Yonghong,Huang, Tiejun,et al. Multi-polarity text segmentation using graph theory. 2008-01-01.

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