LI Zong-yan,SONG Li-mei,XI Jiang-tao,GUO Qing-hua,ZHU Xin-jun,CHEN Ming-lei.A stereo matching algorithm based on SIFT feature and homography matrix[J].Optoelectronics Letters,2015,11(5):390-394
A stereo matching algorithm based on SIFT feature and homography matrix
Author NameAffiliation
LI Zong-yan Key Laboratory of Advanced Electrical Engineering and Energy Technology, Tianjin Polytechnic University, Tianjin 300387, China 
SONG Li-mei Key Laboratory of Advanced Electrical Engineering and Energy Technology, Tianjin Polytechnic University, Tianjin 300387, China 
XI Jiang-tao School of Electrical, Computer and Telecommunications Engineering, University of Wollongong, Keiraville 2500, Australia 
GUO Qing-hua Key Laboratory of Advanced Electrical Engineering and Energy Technology, Tianjin Polytechnic University, Tianjin 300387, China
School of Electrical, Computer and Telecommunications Engineering, University of Wollongong, Keiraville 2500, Australia 
ZHU Xin-jun Key Laboratory of Advanced Electrical Engineering and Energy Technology, Tianjin Polytechnic University, Tianjin 300387, China 
CHEN Ming-lei Key Laboratory of Advanced Electrical Engineering and Energy Technology, Tianjin Polytechnic University, Tianjin 300387, China 
Abstract:
      Aiming at the low speed of traditional scale-invariant feature transform (SIFT) matching algorithm, an improved matching algorithm is proposed in this paper. Firstly, feature points are detected and the speed of feature points matching is improved by adding epipolar constraint; then according to the matching feature points, the homography matrix is obtained by the least square method; finally, according to the homography matrix, the points in the left image can be mapped into the right image, and if the distance between the mapping point and the matching point in the right image is smaller than the threshold value, the pair of matching points is retained, otherwise discarded. Experimental results show that with the improved matching algorithm, the matching time is reduced by 73.3% and the matching points are entirely correct. In addition, the improved method is robust to rotation and translation.
Hits: 4013
Download times: 0
This work has been supported by the National Natural Science Foundation of China (Nos.60808020 and 61078041), the National Science and
View Full Text    Download reader