TY - GEN
T1 - Detection of vehicle beating trajectories using color license plate location
AU - Xu, Hongke
AU - Fang, Jianwu
AU - Hu, Qiaoling
AU - He, Mei
AU - Li, Juan
PY - 2010
Y1 - 2010
N2 - In order to prevent the phenomenon that the lorries take some illegal operations, such as jumping and taking the s-shaped line so as to reduce the vehicle weight when they are passing the highway toll station, and also in order to curtail fees disputes in the meantime, this article studied the algorithm which can detect the vehicle beating trajectory automatically. Firstly, license plates are located by HSI color space and texture features. Secondly, it achieved the position of license plates more exactly with the K-means clustering. Furthermore, plate centroid was calculated by image threshold, morphology and connected component labeling algorithm. Because there is hardly distortion for plate centroid in the image sequence, which can be used for calculating the centroid trajectory between the first image frame and the following image frames, and characterizing the vehicle's movement pattern. In order to utilize the hard disk space which is used for saving the image sequence efficiently, improved track detection method was proposed. Through experiments, trajectories of vehicles can be reflected. And it provided the basis for follow-up study.
AB - In order to prevent the phenomenon that the lorries take some illegal operations, such as jumping and taking the s-shaped line so as to reduce the vehicle weight when they are passing the highway toll station, and also in order to curtail fees disputes in the meantime, this article studied the algorithm which can detect the vehicle beating trajectory automatically. Firstly, license plates are located by HSI color space and texture features. Secondly, it achieved the position of license plates more exactly with the K-means clustering. Furthermore, plate centroid was calculated by image threshold, morphology and connected component labeling algorithm. Because there is hardly distortion for plate centroid in the image sequence, which can be used for calculating the centroid trajectory between the first image frame and the following image frames, and characterizing the vehicle's movement pattern. In order to utilize the hard disk space which is used for saving the image sequence efficiently, improved track detection method was proposed. Through experiments, trajectories of vehicles can be reflected. And it provided the basis for follow-up study.
KW - HSI color model
KW - Image processing
KW - K-means clustering
KW - Texture analysis
KW - Track detection
UR - https://www.scopus.com/pages/publications/77955386944
U2 - 10.1109/CCDC.2010.5498385
DO - 10.1109/CCDC.2010.5498385
M3 - 会议稿件
AN - SCOPUS:77955386944
SN - 9781424451821
T3 - 2010 Chinese Control and Decision Conference, CCDC 2010
SP - 4211
EP - 4216
BT - 2010 Chinese Control and Decision Conference, CCDC 2010
T2 - 2010 Chinese Control and Decision Conference, CCDC 2010
Y2 - 26 May 2010 through 28 May 2010
ER -