[KSCI] Korea Science Citation Index Service

http://dx.doi.org/10.3837/tiis.2020.08.019

A Method of License Plate Location and Character Recognition based on CNN

Fang, Wei (School of Computer & Software, Engineering Research Center of Digital Forensics, Ministry of Education, Nanjing University of Information Science & Technology)
Yi, Weinan (School of Computer & Software, Engineering Research Center of Digital Forensics, Ministry of Education, Nanjing University of Information Science & Technology)
Pang, Lin (School of Computer & Software, Engineering Research Center of Digital Forensics, Ministry of Education, Nanjing University of Information Science & Technology)
Hou, Shuonan (Key Laboratory of Smart Grid of Ministry of Education, Tianjin University)

Publication Information

KSII Transactions on Internet and Information Systems (TIIS) / v.14, no.8, 2020 , pp. 3488-3500 More about this Journal

Abstract

At the present time, the economy continues to flourish, and private cars have become the means of choice for most people. Therefore, the license plate recognition technology has become an indispensable part of intelligent transportation, with research and application value. In recent years, the convolution neural network for image classification is an application of deep learning on image processing. This paper proposes a strategy to improve the YOLO model by studying the deep learning convolutional neural network (CNN) and related target detection methods, and combines the OpenCV and TensorFlow frameworks to achieve efficient recognition of license plate characters. The experimental results show that target detection method based on YOLO is beneficial to shorten the training process and achieve a good level of accuracy.

Keywords

CNN; YOLO; character recognition; license plate recognition; target detection;

Citations & Related Records

Reference

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