TY - GEN
T1 - License Plate Recognition System Based on Deep Learning
AU - Tsai, Tzung Yan
AU - Lu, Zhe Yu
AU - Huang, Ching Chun
PY - 2019/5
Y1 - 2019/5
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85080107797&partnerID=8YFLogxK
U2 - 10.1109/ICCE-TW46550.2019.8991985
DO - 10.1109/ICCE-TW46550.2019.8991985
M3 - Conference contribution
AN - SCOPUS:85080107797
T3 - 2019 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-TW 2019
BT - 2019 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-TW 2019
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 6th IEEE International Conference on Consumer Electronics - Taiwan, ICCE-TW 2019
Y2 - 20 May 2019 through 22 May 2019
ER -