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A stereo matching algorithm based on SIFT feature and homography matrix

Journal Article


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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.

UOW Authors


  •   Li, Zongyan (external author)
  •   Song, Limei (external author)
  •   Xi, Jiangtao
  •   Guo, Qinghua
  •   Zhu, Xin-jun (external author)
  •   Chen, Ming-Lei (external author)

Publication Date


  • 2015

Citation


  • Z. Li, L. Song, J. Xi, Q. Guo, X. Zhu, M. Chen, et al "A stereo matching algorithm based on SIFT feature and homography matrix," Optoelectronics letters, vol. 11, (5) pp. 0390-0394, 2015.

Scopus Eid


  • 2-s2.0-84941034256

Ro Full-text Url


  • http://ro.uow.edu.au/cgi/viewcontent.cgi?article=5391&context=eispapers

Ro Metadata Url


  • http://ro.uow.edu.au/eispapers/4370

Number Of Pages


  • 4

Start Page


  • 0390

End Page


  • 0394

Volume


  • 11

Issue


  • 5

Place Of Publication


  • Germany

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.

UOW Authors


  •   Li, Zongyan (external author)
  •   Song, Limei (external author)
  •   Xi, Jiangtao
  •   Guo, Qinghua
  •   Zhu, Xin-jun (external author)
  •   Chen, Ming-Lei (external author)

Publication Date


  • 2015

Citation


  • Z. Li, L. Song, J. Xi, Q. Guo, X. Zhu, M. Chen, et al "A stereo matching algorithm based on SIFT feature and homography matrix," Optoelectronics letters, vol. 11, (5) pp. 0390-0394, 2015.

Scopus Eid


  • 2-s2.0-84941034256

Ro Full-text Url


  • http://ro.uow.edu.au/cgi/viewcontent.cgi?article=5391&context=eispapers

Ro Metadata Url


  • http://ro.uow.edu.au/eispapers/4370

Number Of Pages


  • 4

Start Page


  • 0390

End Page


  • 0394

Volume


  • 11

Issue


  • 5

Place Of Publication


  • Germany