Share Email Print

Proceedings Paper

Image matching for digital close-range stereo photogrammetry based on constraints of Delaunay triangulated network and epipolar-line
Author(s): K. Zhang; Y. H. Sheng; Y. Q. Li; B. Han; Ch. Liang; W. Sha
Format Member Price Non-Member Price
PDF $14.40 $18.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper Abstract

In the field of digital photogrammetry and computer vision, the determination of conjugate points in a stereo image pair, referred to as "image matching," is the critical step to realize automatic surveying and recognition. Traditional matching methods encounter some problems in the digital close-range stereo photogrammetry, because the change of gray-scale or texture is not obvious in the close-range stereo images. The main shortcoming of traditional matching methods is that geometric information of matching points is not fully used, which will lead to wrong matching results in regions with poor texture. To fully use the geometry and gray-scale information, a new stereo image matching algorithm is proposed in this paper considering the characteristics of digital close-range photogrammetry. Compared with the traditional matching method, the new algorithm has three improvements on image matching. Firstly, shape factor, fuzzy maths and gray-scale projection are introduced into the design of synthetical matching measure. Secondly, the topology connecting relations of matching points in Delaunay triangulated network and epipolar-line are used to decide matching order and narrow the searching scope of conjugate point of the matching point. Lastly, the theory of parameter adjustment with constraint is introduced into least square image matching to carry out subpixel level matching under epipolar-line constraint. The new algorithm is applied to actual stereo images of a building taken by digital close-range photogrammetric system. The experimental result shows that the algorithm has a higher matching speed and matching accuracy than pyramid image matching algorithm based on gray-scale correlation.

Paper Details

Date Published: 28 October 2006
PDF: 15 pages
Proc. SPIE 6419, Geoinformatics 2006: Remotely Sensed Data and Information, 64191W (28 October 2006); doi: 10.1117/12.713275
Show Author Affiliations
K. Zhang, Nanjing Normal Univ. (China)
Y. H. Sheng, Nanjing Normal Univ. (China)
Y. Q. Li, Nanjing Normal Univ. (China)
B. Han, Nanjing Normal Univ. (China)
Ch. Liang, Nanjing Normal Univ. (China)
W. Sha, Nanjing Normal Univ. (China)

Published in SPIE Proceedings Vol. 6419:
Geoinformatics 2006: Remotely Sensed Data and Information
Liangpei Zhang; Xiaoling Chen, Editor(s)

© SPIE. Terms of Use
Back to Top