Moving object detection using genetic Algorithm for traffic Surveillance

The objective of paper is to review the video segmentation and moving object detection methods, organize them into different categories. Object detection and tracking is a stimulating problem. The object identification can identify a moving object and discard unwanted candidate area which does not include an interesting object. The techniques used for the general video segmentation for traffic surveillance using genetic dynamic saliency map (GDSM) and background subtraction. Here combine Genetic Dynamic saliency map (GDSM) and Background subtraction is used for identifies moving object and the maximum distance moved by the object in given group of frames. Experimental results show that the traffic surveillance system can detect moving object.