An Adaptive Combination Resolution Algorithm for Moving Object Vector Graphics Based on Automatic Programming Optimization Algorithm

Abstract

A new moving target adaptive image segmentation algorithm is proposed. On the basis of setting the adaptive tracking wave gate to track the moving target, the adjustment coefficient is adaptively calculated according to the criterion of maximum interclass variance function, and then, the adaptive segmentation of the image is completed by setting the threshold segmentation method. Compared with algorithm, iteration method, and maximum entropy method, the proposed algorithm can not only adapt to a variety of complex backgrounds but also has high precision and high speed. Therefore, it is a practical and effective image segmentation method. As a kind of nonparametric density estimation algorithm, automatic programming optimization algorithm of moving target vector graphic combination and resolution has been widely used in video moving target tracking. The algorithm has fast calculation efficiency and is not sensitive to target deformation and rotation; in the case of a partial shade, it has certain robustness. However, the algorithm moves too fast under clear conditions without considering the direction and speed of the target information, so it is easy to lose tracking when tracking fast moving targets. To solve this problem, a new method based on motion vector analysis and automatic programming optimization of moving target vector graphics combination resolution tracking algorithm is proposed. Firstly, the probability and statistics analysis of motion vectors generated in the process of video coding is carried out to obtain the estimated value of target motion direction and speed. Then, the center position of the candidate region can be split by correcting the combination of moving object vector graphics optimized by automatic programming so that the candidate center position is closer to the actual target center position at the beginning of each search. Compared with the traditional automatic programming optimization algorithm, the new algorithm not only improves the tracking accuracy of the fast-moving target but also reduces the number of search iterations, thus improving the operation efficiency. The algorithm can be applied to the case that video coding and target tracking are calculated simultaneously in the intelligent video surveillance equipment, and the experimental results show that the algorithm is effective and feasible.