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Extraction of Text Alignment by Tensor Voting and its Application to Text Detection  

Lee, Guee-Sang (전남대학교 전자컴퓨터공학부)
Dinh, Toan Nguyen (전남대학교 전자컴퓨터공학부)
Park, Jong-Hyun (전남대학교 전자컴퓨터공학부)
Publication Information
Journal of KIISE:Software and Applications / v.36, no.11, 2009 , pp. 912-919 More about this Journal
Abstract
A novel algorithm using 2D tensor voting and edge-based approach is proposed for text detection in natural scene images. The tensor voting is used based on the fact that characters in a text line are usually close together on a smooth curve and therefore the tokens corresponding to centers of these characters have high curve saliency values. First, a suitable edge-based method is used to find all possible text regions. Since the false positive rate of text detection result generated from the edge-based method is high, 2D tensor voting is applied to remove false positives and find only text regions. The experimental results show that our method successfully detects text regions in many complex natural scene images.
Keywords
tensor voting; text detection; natural scene image; region-based text detection; curve saliency;
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