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Technology of Graphic & Image
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3508-3510

Adaptive license detection algorithm for different conditions

Yang Xiujie1
Li Fang2
1. College of Computer, Chongqing College of Electronic Engineering, Chongqing 401331, China
2. School of Computer Science, Chongqing University, Chongqing 400044, China

Abstract

According to the problem of slow license plate detection and low detection accuracy under different conditions, this paper proposed an improved adaptive morphological closed and open operation to improve the license plate detection algorithm. The algorithm first used the local histogram to equalize the license plate image, and used the adaptive morphological closed operation to smooth all grayscale regions, and then introduced the local adaptive threshold processing to get the smooth image and the separated license plate. Finally, it adopted the morphological open operation to separate the connection parts between the external region and the number of the license plates. The experimental results show that the detection accuracy of the proposed method is higher than other algorithms. At the same time, the average detection time is less than other algorithms. The proposed method is suitable for real-time license plate detection under different conditions.

Foundation Support

重庆市教委课题(KJ1729408)
重庆市教委教改重点项目(162071)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2018.06.0423
Publish at: Application Research of Computers Printed Article, Vol. 36, 2019 No. 11
Section: Technology of Graphic & Image
Pages: 3508-3510
Serial Number: 1001-3695(2019)11-070-3508-03

Publish History

[2019-11-05] Printed Article

Cite This Article

杨秀杰, 李芳. 自适应不同条件的车牌检测算法 [J]. 计算机应用研究, 2019, 36 (11): 3508-3510. (Yang Xiujie, Li Fang. Adaptive license detection algorithm for different conditions [J]. Application Research of Computers, 2019, 36 (11): 3508-3510. )

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Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

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