Abstract:

In order to improve the tracking performance of the low-contrast images, an improved Mean Shift tracking algorithm fusing differential information of images is proposed. The differential image of the origin image is got according to its eight neighborhood differential values. The differential histogram models of the target template and the candidate region are built based on the differential characteristics. The iterative vectors of the central position of the candidate region can be determined by the differential histogram models and the color histogram models. The two iterative vectors can be fused to get a new iterative vector of the improved algorithm. The differential image contains detail information and space position relations, which increases the utilization of information, and enhances the model precision. Simulation results show that the improved algorithm has a better anti-interference performance than conventional methods in complex background, and the stability of the target tracking can be improved.