It is very important to create the background model for image processing.Traditional modeling methods typically use only the gray space

ignoring information from the color space.They do not apply to the complex transportation system.In order to obtain dynamic vehicle information and colored road information for further analysis

we propose a non-parametric road modeling approach based on color spatial clustering in this article. The approach is developed according to the characteristics of pixel distribution in traffic scenes. The modeling process is abstracted as a color spatial clustering process in the time axis. According to the color distortion theory

we define a cluster interval as a cylinder whose axis is the attachment of the clustering center and the origin in color space. Meanwhile

for each pixel the clustering center number is selected adaptively according to the scene’s complexity and change frequency. In this way

the precision improves and the detection is efficient.