<title>Locating Fast-Moving Objects In TV-Images In The Presence Of Motion Blur</title>

A novel algorithm on the basis of nonlinear filtering is described, that overcomes difficulties and has succeeded in locating with high accuracy objects, whose images move at speeds of 1000 pixels/sec.

Abstract

When computer vision is used for the real-time control of dynamic systems, one difficulty arises from the fact that TV-cameras integrate the incoming light over a time interval equivalent to one frame period. If an observed object moves fast enough, its image will deteriorate in two ways: the edges will be blurred and the contrast will diminish. This causes conventional edge detectors or thresholding methods to break down. This paper describes a novel algorithm on the basis of nonlinear filtering, that overcomes these difficulties and has succeeded in locating with high accuracy objects, whose images move at speeds of 1000 pixels/sec. Experimental results obtained by simulation and by controlling real objects are reported. A similar algorithm can be used to estimate the velocity of an object from the degree of motion blur of its image.