Gray target tracking algorithm based on edge information

Abstract

To precisely track the gray targets undergoing drastic changes in the image sequence,a new tracking algorithm based on edge information was proposed. Firstly,obtained by the two-concentric-circularwindow operator,a nonlinear edge detection algorithm was proposed to get high quality edge information. Secondly,a novel method to construct feature space by synthesizing edge images was proposed in order to solve the problem that single edge feature space was not able to characterize the target thoroughly. The proposed method provided enough information to construct target model. Then,an approach to construct the target model with the kernel-based estimation method was proposed in constructed feature space. In target localization stage,the target position was preliminarily predicted by Kalman filter,and then the Mean Shift algorithm is utilized to locate the target in the region around the predicted position. Finally,a new dynamic model update strategy based on morphological operations was proposed. It can offer the proposed algorithm the ability to obtain precise target region and automatically adjust to the changing target size and target shape. Experimental results demonstrate that the proposed algorithm can perform well in image sequences where the targets undergo drastic changes. Meanwhile,the proposed algorithm can obtain the precise target region,and the track window can automatically adjust to the changing target size and target shape.