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Journal of Electronic Imaging

License plate detection in an open environment by density-based boundary clustering
Author(s): Jiangmin Tian; Guoyou Wang; Jianguo Liu; Yuanchun Xia
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Paper Abstract

Due to the variation of background, illumination, and view point, license plate detection in an open environment is challenging. We propose a detection method by boundary clustering. To start with, a boundary map is obtained through Canny edge detector and removal of unwanted horizontal background edges. Second, boundaries are classified into different clusters by a density-based approach. In the approach, the density of each boundary is defined by the total gradient intensity of its neighboring and reachable boundaries. Also, the cluster centers and the number of them are determined automatically according to a minimum-distance principle. At last, a set of horizontal candidate regions with accurately located borders are extracted for classification. The classifier is trained on the histogram of oriented gradient feature by a linear support vector machine model. Experiments on three public datasets including images captured under different scenarios demonstrate that the proposed method outperforms several state-of-the-art methods in detection accuracy and its performance in efficiency is also comparable.

Paper Details

Date Published: 27 May 2017
PDF: 11 pages
J. Electron. Imag. 26(3) 033017 doi: 10.1117/1.JEI.26.3.033017
Published in: Journal of Electronic Imaging Volume 26, Issue 3
Show Author Affiliations
Jiangmin Tian, Huazhong Univ. of Science and Technology (China)
Guoyou Wang, Huazhong Univ. of Science and Technology (China)
Jianguo Liu, Huazhong Univ. of Science and Technology (China)
Yuanchun Xia, Huazhong Univ. of Science and Technology (China)


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