Research on space occupation recognition method of fuel vehicles in charging station based on license plate recognition algorithm

Lei Chi; Han Xie; Shouqin Wang; Chaoyi Cheng; Xiujuan Yuan; Yajing Zhang

doi:10.1117/12.2647067

7 September 2022 Research on space occupation recognition method of fuel vehicles in charging station based on license plate recognition algorithm

Lei Chi, Han Xie, Shouqin Wang, Chaoyi Cheng, Xiujuan Yuan, Yajing Zhang

Author Affiliations +

Proceedings Volume 12329, Third International Conference on Artificial Intelligence and Electromechanical Automation (AIEA 2022); 123291Q (2022) https://doi.org/10.1117/12.2647067
Event: Third International Conference on Artificial Intelligence and Electromechanical Automation (AIEA 2022), 2022, Changsha, China

Abstract

With the rapid development of new energy vehicles, problems such as “charging difficulty” are becoming increasingly prominent. The charging space is occupied by fuel vehicles, resulting in the inability of new energy vehicles to charge after they arrive at the charging station. This paper proposes a license plate recognition algorithm model which combines the three steps of vehicle detection, license plate detection, and license plate recognition, which improves the robustness of license plate recognition in complex scenes. In view of the lack of Chinese license plate data, the data enhancement method is adopted to improve the recognition accuracy of Chinese provincial abbreviations and common color license plates such as blue, green, and yellow. According to the characteristics of a small license plate target and easy rotation in the license plate recognition task, the WPOD-NET network is selected for license plate detection. Finally, the license plates of new energy vehicles and fuel vehicles are distinguished by recognizing the color and law of license plates, so as to provide supporting information for the generation of fuel vehicle occupancy alarm. In this paper, the data collected by the cameras of some charging stations in a city are used for verification. The verification results show that the accuracy of oil vehicle occupancy recognition is as high as 97%.

Citation Download Citation

Lei Chi, Han Xie, Shouqin Wang, Chaoyi Cheng, Xiujuan Yuan, and Yajing Zhang "Research on space occupation recognition method of fuel vehicles in charging station based on license plate recognition algorithm", Proc. SPIE 12329, Third International Conference on Artificial Intelligence and Electromechanical Automation (AIEA 2022), 123291Q (7 September 2022); https://doi.org/10.1117/12.2647067

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KEYWORDS

Detection and tracking algorithms

Target detection

Optical character recognition

Target recognition

Feature extraction

Image enhancement

Image processing

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