Two perspective images of single scene taken by uncalibrated perspective cameras are constrained by the epipolar geometry

which is the key to many problems of computer vision.This paper addresses the problem of robust estimating the epipolar geometry employing a new method based on messy genetic algorithm

which use each gene to stand for a pair of correspondences

and take every chromosome as a minimum subset for epipolar geometry estimation.The method would eventually converge to a globally optimal solution and is relatively unaffected by the outliers.Experiments with both synthetic data and real images show that our method is more robust and precise than other typical methods because it can efficiently detect and delete the bad corresponding points

which include both bad locations and false matches.