For region matching in stereoscopic images

most algorithms will be affected by the factors such as regions occlusion

regions warping and lighting condition.So the traditional constraint conditions

like order constraint

unique constraint

epipolar constraint and adjacent constraint

may be violated by these cases. In past few years a new algorithm based on the relative position constraint (RPC) between regions is proposed which can overcome most of the problems mentioned above

but it has not satisfying performance in matching occluded objects in the stereo images. Therefore

there remain false matches and miss correspondences in the final results. In this paper

a novel algorithm using both the relative position constraint and the new cost function on the basis of regions center distance and Zernike moments theory is proposed. Furthermore the adjustable weights of cost function are dynamically estimated according to the distance between the centers of two matching regions. Finally

the proposed region matching algorithm is illustrated by three synthesized stereo images

with a comparison to the present algorithm and the superiority of the new region matching algorithm over the present algorithm is experimentally verified.