License Plate Recognition System Based on Deep Learning

被引：1
|
作者：
Tsai, Tzung-Yan [1 ]
Lu, Zhe-Yu [1 ]
Huang, Ching-Chun [1 ]
机构：
[1] Natl Chung Cheng Univ, Chiayi, Taiwan
来源：
2019 IEEE INTERNATIONAL CONFERENCE ON CONSUMER ELECTRONICS - TAIWAN (ICCE-TW) | 2019年
关键词：
D O I：
10.1109/icaica50127.2020.9182382
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
We proposed a license plate recognition system based on the YOLOv2 framework. It contains a plate detection network and a plate recognition network. When we input a car image, the first network can detect the position of license plates, and the second network can recognize the characters within the detected plate. Besides, we modify the loss function to train the YOLOv2 for character recognition. Finally, the system outputs the predictive plate numbers after post-processing. Currently, the recognition accuracy can reach 97%, and at least 5 pictures can be recognized in one second.
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页数：2
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