TY - GEN
T1 - Extracting auto-correlation feature for license plate detection based on AdaBoost
AU - Tan, Hauchun
AU - Deng, Yafeng
AU - Chen, Hao
PY - 2008
Y1 - 2008
N2 - In this paper, a new method for license plate detection based on AdaBoost is proposed. In the proposed method, auto-correlation feature, which is ignored by previous learning-based method, is introduced to feature pool. Since that there are two types of Chinese license plate, one type is deeper-background- lighter-character and the other is lighter-background-deeper-character, training a detector cannot convergent. To avoid this problem, two detectors are designed in the proposed method. Experimental results show the superiority of proposed method.
AB - In this paper, a new method for license plate detection based on AdaBoost is proposed. In the proposed method, auto-correlation feature, which is ignored by previous learning-based method, is introduced to feature pool. Since that there are two types of Chinese license plate, one type is deeper-background- lighter-character and the other is lighter-background-deeper-character, training a detector cannot convergent. To avoid this problem, two detectors are designed in the proposed method. Experimental results show the superiority of proposed method.
KW - AdabBoost
KW - Auto-correlation
KW - License Plate Detection
UR - http://www.scopus.com/inward/record.url?scp=58149085585&partnerID=8YFLogxK
U2 - 10.1007/978-3-540-88906-9_10
DO - 10.1007/978-3-540-88906-9_10
M3 - Conference contribution
AN - SCOPUS:58149085585
SN - 3540889051
SN - 9783540889052
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 72
EP - 79
BT - Intelligent Data Engineering and Automated Learning - IDEAL 2008 - 9th International Conference, Proceedings
PB - Springer Verlag
T2 - 9th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2008
Y2 - 2 November 2008 through 5 November 2008
ER -