An Efficient Real Time Moving Object Detection Method for Video Surveillance System

Moving object detection has been widely used in diverse discipline such as intelligent transportation systems, airport security systems, video monitoring systems, and so on. In this paper, we propose an efficient moving object detection method using enhanced edge localization mechanism and gradient directional masking for video surveillance system. In our proposed method, gradient map images are initially generated from the input and background images using a gradient operator. The gradient difference map is then calculated from gradient map images. The moving object is then detected by using appropriate directional masking and thresholding. Simulation results indicate that the proposed method consistently performs well under different illumination conditions including indoor, outdoor, sunny, and foggy cases. Moreover, it outperforms well known edge based method in terms of detecting moving objects and error rate. Moreover, the proposed method is computationally faster and it is applicable for detecting moving object in real-time.