A single-target license plate detection with attention

Wenyun Li; Chi-Man Pun

doi:10.1117/12.2624588

30 April 2022 A single-target license plate detection with attention

Wenyun Li, Chi-Man Pun

Proceedings Volume 12177, International Workshop on Advanced Imaging Technology (IWAIT) 2022; 1217720 (2022) https://doi.org/10.1117/12.2624588
Event: International Workshop on Advanced Imaging Technology 2022 (IWAIT 2022), 2022, Hong Kong, China

Abstract

In wild scenes, the detection of license plates (LP) is a fundamental task in realistic intelligent transportation applications. However, most existing license plates detection models are not designed for license plate detection tasks specifically. As a standard single target object detection task, just adapting the multiple detection method to license plate detection may not be a good choice. Hence, in this paper, we choose a single detection method of state-of-the-art RetinaNet, which works well in unconstrained environment. By adding the attention module to the neural networks, we choose a more proper bbox loss function of CIoU. In the experiments, we test and evaluate on the largest Chinese license plate dataset (CCPD). Experimental results show that our proposed method can achieve better performance with very high accuracy of 99.75%, compared with other methods.

Citation Download Citation

Wenyun Li and Chi-Man Pun "A single-target license plate detection with attention", Proc. SPIE 12177, International Workshop on Advanced Imaging Technology (IWAIT) 2022, 1217720 (30 April 2022); https://doi.org/10.1117/12.2624588

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