Detecting text in license plates using a novel MSER-based method

Admi Mohamed, El Fkihi Sanaa and Rdouan Faizi

International Journal of Data Analysis Techniques and Strategies, 2020, vol. 12, issue 4, 335-348

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).

Keywords: text detection; MSER; circle overlapping; DBSCAN; license plate detection. (search for similar items in EconPapers)
Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:ids:injdan:v:12:y:2020:i:4:p:335-348

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