Adaptive Detection of Moving Vehicle Based on On-line Clustering

Detection of moving vehicles plays a very important role in Intelligent Transport. Aiming at the deficiency of moving vehicle detection, we proposed the adaptive detection method of moving vehicles based on the online clustering. First extracts background adaptively using a new online clustering algorithm which does not need to set any parameters when extract the background image. Then adaptively select the background updating rate according to the road disturbance of background and illumination changes after background building is completed. Finally, realize correct and complete moving object segmentation through foreground detection using background difference. Experimental results show that the proposed method is able to detect moving target accurately in the transport video, it not only has good self-adaptability and real-time but also insensitive to the light changes and background interference.