Scene text detection via stroke width

In this paper, we propose a novel text detection approach based on stroke width. Firstly, a unique contrast-enhanced Maximally Stable Extremal Region(MSER) algorithm is designed to extract character candidates. Secondly, simple geometric constrains are applied to remove non-text regions. Then by integrating stroke width generated from skeletons of those candidates, we reject remained false positives. Finally, MSERs are clustered into text regions. Experimental results on the ICDAR competition datasets demonstrate that our algorithm performs favorably against several state-of-the-art methods.