TY - GEN
T1 - Research of license plate recognition under complex environment
AU - Gao, Feng
AU - Dai, Zhong Jian
AU - Zhou, Kun
AU - Dai, Ya Ping
PY - 2014
Y1 - 2014
N2 - In order to improve the license plate recognition accuracy under complex environment, a new license location algorithm combining vertical edge detection, color information of the license plate and mathematical morphology is presented in this paper. For balance of computing load and recognition accuracy, a "200-d" character feature rule is designed, and the "200-d" feature is used as the input of BP neural network to recognize the characters. Based on the above-mentioned methods, a license plate recognition system is set up, which can locate and recognize the license plate effectively, even when the resolution of pictures and the position of vehicles in the pictures are not fixed. Experimental results indicate that the recognition rate of the algorithm reaches 90.5%.
AB - In order to improve the license plate recognition accuracy under complex environment, a new license location algorithm combining vertical edge detection, color information of the license plate and mathematical morphology is presented in this paper. For balance of computing load and recognition accuracy, a "200-d" character feature rule is designed, and the "200-d" feature is used as the input of BP neural network to recognize the characters. Based on the above-mentioned methods, a license plate recognition system is set up, which can locate and recognize the license plate effectively, even when the resolution of pictures and the position of vehicles in the pictures are not fixed. Experimental results indicate that the recognition rate of the algorithm reaches 90.5%.
KW - Character feature extraction
KW - Edge detection
KW - License plate color information
KW - License plate recognition
KW - Neural network
UR - http://www.scopus.com/inward/record.url?scp=84905842878&partnerID=8YFLogxK
U2 - 10.4028/www.scientific.net/AMR.989-994.2569
DO - 10.4028/www.scientific.net/AMR.989-994.2569
M3 - Conference contribution
AN - SCOPUS:84905842878
SN - 9783038351733
T3 - Advanced Materials Research
SP - 2569
EP - 2575
BT - Materials Science, Computer and Information Technology
PB - Trans Tech Publications Ltd.
T2 - 4th International Conference on Materials Science and Information Technology, MSIT 2014
Y2 - 14 June 2014 through 15 June 2014
ER -