Abstract
In this paper, a hybrid approach is proposed to detect texts in natural scenes. It is performed by the following steps: Firstly, the edge map and the text saliency region are obtained. Secondly, the text candidate regions are detected by connected components (CC) based method and are identified by an off-line trained HOG classifier. And then, the remaining CCs are grouped into text lines with some heuristic strategies to make up for the false negatives. Finally, the text lines are broken into separate words. The performance of the proposed approach is evaluated on the location detection database of ICDAR 2003 robust reading competition. Experimental results demonstrate the validity of our approach and are competitive with other state-of-the-art algorithms.
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