Stereo correspondence using geometric relational matching

A new geometric relational matching approach is proposed to solve the stereo correspondence problem. The first distinct features are extracted in a pair of stereo images using a feature extractor. Then a newly developed window-based feature point detector is used to detect feature points from the extracted feature in both images. Feature points are connected with two points to form a straight line in both images. A match function representing the requirements of the epipola and disparity constraints in both images is proposed for straight line matching. Important information can be obtained front the parameter values attached to each line, such as distance and orientation. Information contained in the match function is used to determine straight-line correspondence. The method described here takes a unique approach to match straight line. After that straight-line correspondence is established using the match function values in the left image and corresponding ones in the right image. Triplets of matched points are used to construct a model polygon in the left image. Then the entire right image is searched by an exhaustive search method to find a matching polygon. The computational complexity of the proposed method is proportional to the number of detected feature points in the image pair. Experimental results indicate that the method performs well for a variety of stereo images, and it is suitable for many applications.