A decade ago we are encountering more applications in video surveillance to deliver issues identified with social needs. The significance of open security is developing, and video observation frameworks are progressively far reaching devices for checking, the board, and law implementation in open zones. In this paper, we proposes computer vision techniques to recognize moving objects from video to follow continuously as articles experienced in the indoor and outside condition. Nearness is a reality of being close to other and legitimizes closeness. Framework tracks grouped items against a domain comprising of objects of shifting sizes, shapes and hues. At first foundation demonstrating is performed utilizing the capacity which gathered the foundation outlines from mean and standard deviation of first N outlines. Each critical change in the article appearance from that point, because of new object, old item vanishing is followed dependent on the vicinity of the objective. The visual similarity is resolved as for the recognized item in the past video outline and the last edge detection.