Abstract
A new license plate detection method is proposed in this paper. The proposed approach consists of three steps: the first step aims to delete some details in the input image by converting it to a grey-level image and inverse it (negative) and then use MSER for the extraction of text in candidate regions. The second step is based on a dynamic grouped DBSCAN algorithm for a fast classification of the connected region, and the outer tangent of circles intersections for filtering regions with the same orientations. Finally, a geometrical and statistical character filter is used to eliminate false detections in the third step. Experimental results show that our approach performs better and achieves a better detection than that proposed by Yin et al. (2014).
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