Object Detection And Shadow Removal In Visual Surveillance

Development of the computer vision technology, the electronic and the communication technology, has made the intelligent visual surveillance system an increasingly important safe defense way. Both its history and current situation is summarized here, then, the algorithms for the moving object detection and the shadow removal are all discussed.As the initial stage in the visual data processing, moving object detection is a key point, also, a difficult research area. After carefully study of moving object detection methods used presently, a more reliable algorithm is determined through experiments, that is, the background difference method based on mixed Gauss model. It has been proved in experiments that the mixed Gauss background model is more robust to the brightness change, repeated movements of the elements in a scene, slowly moving object, and annexing or removing object in a scene.A new shadow detection algorithm using the first-order gradient is presented, being supported by the mix-Gauss background model. The shadow detection discriminant based on first-order gradient is gained by the Sobel operator's gradient background model. The threshold value of the discriminant, which has a stronger auto-adaption, is produced by the statistical gradient background model. This algorithm is combined to the shadow detection algorithm based on RGB color space, just to increase the detection precision in the shadow area. Accurate extraction of a moving object is realized by reconstructing its movement.