Novel Algorithms for Estimating Motion Characteristics within a Limited Sequence of Images

Abstract. Two novel algorithms for estimating the motion characteristics of the object in dynamic scene by processing a limited sequence of images are presented in this paper. The first algorithm is based on computation of space-temporal gradients of consecutive frames of video stream, another one has been designed for fast detection of motion by processing of principal corners of objects in real time applications. For quantitative estimation of motion characteristics, the novel segment and neighbours matching technique has been proposed. The method uses the concept of fuzzy sets and membership functions, which permits high-speed recognition and efficient interpretation of the patterns with significant level of noise and distortions. The introduced algorithms have been tested in order to evaluate their velocity, utility and efficiency.