Reliable image matching via modified Hausdorff distance with normalized gradient consistency measure

Abstract

Reliable image matching is important to many problems in computer vision, image processing and pattern recognition. Hausdorff distance and many of its variations have been employed for image matching with success. In this paper we propose an improved image matching method based on a modified Hausdorff distance with normalized gradient consistency measure. The proposed new image matching algorithm integrates the geometric Hausdorff distance with the photometric intensity gradient information to obtain a better image similarity measure. To show the improvement of the proposed algorithm, we test it with some previous image matching methods on the problem of face recognition under lighting changes. Experimental results show the proposed method produces more accurate face recognition than the previous methods.