A study on license plate recognition based on convolutional neural network

Xiangui Shi; Xiaole Wang; Tao Chen; Cong Qian; Yiming Liu

doi:10.1117/12.2660709

3 February 2023 A study on license plate recognition based on convolutional neural network

Xiangui Shi, Xiaole Wang, Tao Chen, Cong Qian, Yiming Liu

Proceedings Volume 12511, Third International Conference on Computer Vision and Data Mining (ICCVDM 2022); 125113F (2023) https://doi.org/10.1117/12.2660709
Event: Third International Conference on Computer Vision and Data Mining (ICCVDM 2022), 2022, Hulun Buir, China

Abstract

With the rapid development of advanced technologies such as artificial intelligence and Internet of Things, intelligent traffic management has been widely used. License plate recognition technology is particularly important in intelligent traffic management as the unique identification of vehicles, but due to the influence of natural environment, recognition angle, image clarity, size of license plate and other factors, the traditional license plate recognition technology is less robust and difficult to accurately identify the number plate number. In this paper, we describe a license plate recognition technique implemented by constructing Convolutional Neural Networks (CNN), which is able to recognize license plate numbers more accurately and has certain significance for further research on deep learning in the field of intelligent traffic management.

Citation Download Citation

Xiangui Shi, Xiaole Wang, Tao Chen, Cong Qian, and Yiming Liu "A study on license plate recognition based on convolutional neural network", Proc. SPIE 12511, Third International Conference on Computer Vision and Data Mining (ICCVDM 2022), 125113F (3 February 2023); https://doi.org/10.1117/12.2660709

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KEYWORDS

Image segmentation

Convolution

Image processing

Convolutional neural networks

Data modeling

Feature extraction

Neural networks

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