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Proceedings Paper

Design and implementation of license plate recognition system based on deep learning
Author(s): Bianlian Zhang; Zhaohua Liu; Xiaoli Zhang
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Paper Abstract

This paper is based on the deep learning license plate recognition system, which is a method of deep learning in the recognition of license plates.In the recognition of license plates, improved Convolutional-Neural-Network (CNN) is used to identify the accuracy and speed of recognition. The experimental results show that the application of convolutional neural network in license plate recognition can effectively improve the recognition rate of the license plate in various environments such as pollution, insufficient illumination, etc. This recognition rate is improved by means of a large training character set. The more character forms included in the character set, the higher the recognition rate, the more the license plate character recognition rate can reach 98% or more. In addition, for the trained convolutional neural network, including the license plate extraction and pre-processing recognition speed can also reach less than 30 ms.

Paper Details

Date Published: 31 January 2020
PDF: 6 pages
Proc. SPIE 11427, Second Target Recognition and Artificial Intelligence Summit Forum, 1142712 (31 January 2020); doi: 10.1117/12.2551026
Show Author Affiliations
Bianlian Zhang, Xi'an Univ. (China)
Zhaohua Liu, Xi'an Univ. (China)
Xiaoli Zhang, Xi'an Univ. (China)

Published in SPIE Proceedings Vol. 11427:
Second Target Recognition and Artificial Intelligence Summit Forum
Tianran Wang; Tianyou Chai; Huitao Fan; Qifeng Yu, Editor(s)

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