改进的光流运动图像分析方法及其应用

Abstract

For the problems of low motion estimation accuracy and easy to be affected by various interferences such as object surface structure change,background light disturbance etc,when solving the basic optical flow constraint equation with the traditional algorithm,an improved optical flow algorithm with five-confidence-point restraint based on gradient threshold has been put forward in this paper.The five-confidence-point weighted method was applied to calculate the time and space gradient value of each image pixel,reducing noise effect on it,and gradient and gradient threshold was adopted to process the basic optical flow constraint equation,so that the interference data which will disturb the motion estimation in the optical flow field were eliminated,and the motion estimation accuracy of motion image was improved.The experiments have been carried out by the traditional algorithm and the improved one respectively for global and local movements.The contrastive analysis shows that this improved optical flow algorithm,which can figure both scene global motion and local motion in the scene,has the advantages of not only a high accuracy of motion estimation and a strong anti-interference,but also a better robustness and convergence compared with the traditional one,as well as one-third of computaion time shortened.It can be expected that this algorithm will be of potential application in driving environment sensing and traffic flow analysis.