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Scene text extraction, i.e., segmenting text pixels from background, is an important step before the text can be recognized. It is a challenging problem due to the cluttered background and the variation of lighting. In this paper, we propose a seed-based segmentation method that can automatically judge the text polarity, extract seed points of text and background, and segment texts by semi-supervised...
In this paper, we propose an efficient scene text localization method using gradient local correlation, which can characterize the density of pair wise edges and stroke width consistency to get a text confidence map. Gradient local correlation is insensitive to the gradient direction and robust to noise, small character size and shadow. Based on the text confidence map, the regions with high confidence...
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