An optical flow and inter-frame block-based histogram correlation method for moving object detection

Moving object detection is very important for video surveillance. In this paper, we present a new real time motion detection algorithm that is based on the integration of optical flow and inter-frame block-based histogram correlation method to achieve better performance. The optical flow method is used to detect any movement under the background and the inter-frame block-based histogram correlation method is used to eliminate the background information and separate the moving object from it. The biggest advantage of this algorithm is that it does not need to learn the background model from hundreds of images and can handle quick image variations without prior knowledge about the object size and shape. The algorithm has high capability of anti-interference and preserves high accurate rate detection at the same time. The effectiveness of the proposed algorithm for motion detection is demonstrated in a simulation environment and the evaluation results are reported in this paper.