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10 November 2020 A novel tilting location and character segmentation algorithm for Chinese license plates
Xiangyu Deng, Ran Zhang, Wenjuan Qin
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Proceedings Volume 11584, 2020 International Conference on Image, Video Processing and Artificial Intelligence; 115840N (2020) https://doi.org/10.1117/12.2580508
Event: Third International Conference on Image, Video Processing and Artificial Intelligence, 2020, Shanghai, China
Abstract
License plate (LP) location is a key technology in the process of license plate recognition (LPR). How to realize the LP location and character segmentation of complex vehicle images has always been a hot issue in the research of intelligent transportation systems. In this paper, a novel LP location method combining the connected domain (CD) slope detection method and the dynamic template matching method is proposed for the complicated situations that the tilt angle of the LP is too large, the LP is defaced, the LP frame is unclear and the characters are adhesive or defective. Firstly, the method uses the CD slope detection method to find out the equal-slope CD of the LP characters in the optimal segmentation image after pre-processing and determine the tilt angle. Then locate the horizontal region of the LP and realize the tilt correction. After that, the proposed the dynamic template matching method is used to locate the vertical position of the LP and segment the LP characters accurately. Finally, the experiment proves that the proposed algorithm reduces the recognition difficulty of the LP with the above problems, and has the characteristics of fast speed, accurate recognition, good adaptability and strong anti-interference. It also has good versatility and scalability for the newly introduced new energy LP with 8-character.
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Citation Download Citation
Xiangyu Deng, Ran Zhang, and Wenjuan Qin "A novel tilting location and character segmentation algorithm for Chinese license plates", Proc. SPIE 11584, 2020 International Conference on Image, Video Processing and Artificial Intelligence, 115840N (10 November 2020); https://doi.org/10.1117/12.2580508
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KEYWORDS
Image segmentation
Image processing algorithms and systems
Detection and tracking algorithms
Adhesives
Image processing
Intelligence systems
Edge detection
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