Geometric feature-based matching in stereo images

Presents a geometric feature-based matching approach 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 epipolar and disparity constraints in both images is proposed for straight line matching. After that straight-line correspondence is established using the match function values in the left image and corresponding ones in the right image. Feature points are ordered in both images using a geometric transformation and stored in a database in increasing order. Triplets of ordered 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. A disparity test is applied to ensure that no matched feature point in an image can be rematched with another feature point. Experimental results indicate that the method performs well for real stereo images and it is suitable for many applications