In video surveillance, there are many interference factors such as target changes, complex scenes, and target deforma-tion in the moving object tracking. In order to resolve this issue, based on the comparative analysis of several common moving object detection methods, a moving object detection and recognition algorithm combined frame difference with background subtraction is presented in this paper. In the algorithm, we first calculate the average of the values of the gray of the continuous multi-frame image in the dynamic image, and then get background image obtained by the statis-tical average of the continuous image sequence, that is, the continuous interception of the N-frame images are summed, and find the average. In this case, weight of object information has been increasing, and also restrains the static back-ground. Eventually the motion detection image contains both the target contour and more target information of the tar-get contour point from the background image, so as to achieve separating the moving target from the image. The simu-lation results show the effectiveness of the proposed algorithm.
Yang, K., Cai, Z., & Zhao, L. (2013). Algorithm Research on Moving Object Detection of Surveillance Video Sequence. Optics and Photonics Journal, 03(02), 308–312. https://doi.org/10.4236/opj.2013.32b072