An Area and Feature-Based Matching Method for 3D Reconstruction

This paper proposes a junction detection method in images by searching for the intersection of the linear ridges in gradient domain, and then presents a stereo matching method based on this new algorithm of junction detection, in order to meet the need of 3D reconstruction system. The images are uncalibrated and can be taken by different cameras or a single camera at different time instants. The proposed method adopts a strategy from rough matching to delicate matching. In the first matching process, the probability of mismatching is decreased on the cost of reducing the matching number. Thus, only the junctions with high strength are matched and the direction angles of the junctions´ branches are used as a matching constraint. Then, the fundamental matrix is estimated by RANSAC and normalized 8-point algorithm. At last, the parameters of the junction detection are modified and the Harries corner detection is added to get more feature points. More matching points could be obtained through the guide of the fundamental matrix in the second matching process. The experiment results show that this algorithm has good performance on speed, accuracy and could obtain more edge matching points.