Intelligent Video Surveillance System Using Background Subtraction Technique and its Analysis

摘要

Visual surveillance systems start with motion detection or tracking. This motion object detection method attempts to locate connected regions that define or relate the moving objects within the scene; like frame-to-frame difference, background subtraction and motion analysis, For Intelligent Video Surveillance System Using Background Subtraction Technique and its Analysis this paper have used background subtraction using dynamic threshold and mixture of Gaussian. Here three different methods are used effectively for object detection and compared their basis of performance on the accurate detection. Here the techniques frame differences, dynamic threshold based detection and mixture of Gaussian model used. After the object foreground detection, the parameters like speed, velocity motion are determined. For this, the existing methods are dependent on static background for a short interval or time. In static threshold environment, due to noise the motion pattern are distinctive and hardly tolerated, which leads to a high level false positive rates compared to the previous models. To remove the unwanted pixel, filtering and morphological process are used in dynamic threshold environment. We are using an intelligence background subtraction algorithm for temporally dynamic texture scenes using a mixture of Gaussian along with this dynamic threshold, which gives an ability of greatly rarefying color variations due to the background motions but still highlighting moving objects. This proposed method proves to be an effective background subtraction technique with dynamic threshold in a dynamic environment comparing with several competitive methods and parameters after evaluating.