Abstract

Study on extraction of image features of detectionand location based on video motion nuclear method

Author(s): Wang xiaojun, Pan feng, Wang weihong

complex applications, without and different target features directly affects the detection of selected tracking algorithm. So far still does not exist a universal algorithm for perfect can be suitable for various applications, so the detection and tracking of moving targets is still a valuable research subject of. The research work in this paper is in the field, the moving target detection spatiotemporal correlation and difference contour tracking algorithm based on a fixed background. The algorithm in the background under the condition of fixed to pay a smaller time complexity, the target detection and tracking has a good effect, so it has higher application value. Based on solving the detection and location of moving target tracking in real-time and accuracy requirements, a new moving target detection spatiotemporal correlation and difference contour tracking scheme based on the practical implementation, at the same time analysis and the experimental results are given. In the moving target tracking, tracking method is mainly traditional correlation method target based on template matching. The matching process is time consuming, so the actual use of more of the improved algorithm of correlation method, the improved algorithm attempts to improve the efficiency of feature matching and search range, and also achieved a certain effect, the some excellent tracking algorithm. This paper presents an improved active contour model tracking algorithm, improve the tracking efficiency and quality, the algorithm first from the frame difference detection results to find the moving target coarse contour, and then the convergence of coarse contour by using improved Snake algorithm, the right edge to get the target in the course of the campaign, in order to achieve the tracking of moving objects


Share this       

Share this Page.

Table of Contents

Scimago Journal Rank

SCImago Journal & Country Rank

Flyer