TY - GEN
T1 - Mean shift for accurate number plate detection
AU - Jia, Wenjing
AU - Zhang, Huaifeng
AU - He, Xiangjian
PY - 2005
Y1 - 2005
N2 - This paper presents a robust method for number plate detection, where mean shift segmentation is used to segment color vehicle images into candidate regions. Three features are extracted in order to decide whether a candidate region contains a number plate, namely, rectangularity, aspect ratio, and edge density. Then, the Mahalanobis classifier is used with respect to the above three features to detect number plate regions accurately. The experimental results show that our algorithm produces high robustness and accuracy.
AB - This paper presents a robust method for number plate detection, where mean shift segmentation is used to segment color vehicle images into candidate regions. Three features are extracted in order to decide whether a candidate region contains a number plate, namely, rectangularity, aspect ratio, and edge density. Then, the Mahalanobis classifier is used with respect to the above three features to detect number plate regions accurately. The experimental results show that our algorithm produces high robustness and accuracy.
UR - http://www.scopus.com/inward/record.url?scp=33646795966&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:33646795966
SN - 0769523161
SN - 9780769523163
T3 - Proceedings - 3rd International Conference on Information Technology and Applications, ICITA 2005
SP - 732
EP - 737
BT - Proceedings - 3rd International Conference on Information Technology and Applications, ICITA 2005
T2 - 3rd International Conference on Information Technology and Applications, ICITA 2005
Y2 - 4 July 2005 through 7 July 2005
ER -