NDLI: Novel License Plate Detection Method for Complex Scenes

Content Provider	IEEE Xplore Digital Library
Author	Runmin Wang Nong Sang Ruolin Wang Xiaoqin Kuang
Copyright Year	2013
Description	Author affiliation: Sch. of Autom., Huazhong Univ. of Sci. & Technol., Wuhan, China (Runmin Wang; Nong Sang; Xiaoqin Kuang) \|\| Sch. of Civil Eng., Wuhan Univ., Wuhan, China (Ruolin Wang)
Abstract	In this paper, a novel license plate detection method is proposed. There are three key steps in our method, i.e. image preprocessing, license plate detection and license plate confirmation. First, the noises are removed and the diversities of license plate forms are unified through image preprocessing. And then, the license plates are detected roughly by using the cascade AdaBoost classifier. Finally, the gradient images are binarized, and the connected component analysis will be adopted to remove some false plates. Meanwhile, the offline trained Support Vector Machine (SVM) classifier is adopted to confirm the license plate candidates in further. The promising results of the proposed method is verified by experiments on a challenging database.
Starting Page	318
Ending Page	322
File Size	705021
Page Count	5
File Format	PDF
ISBN	9780769550503
DOI	10.1109/ICIG.2013.69
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-07-26
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Support vector machines Image color analysis cascade detection scheme Image edge detection connected component analysis license plate detection Licenses Feature extraction Colored noise SVM classifier Vehicles
Content Type	Text
Resource Type	Article

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