Scientific- Research Quarterly of Geographical Data (SEPEHR)

Scientific- Research Quarterly of Geographical Data (SEPEHR)

Implementation of a Three-Dimensional Matching for Digital Photography

Document Type : Research Paper

Author
Amir Saeed Homaiinejad
Educational Department of Surveying, K. N. Toosi University of Technology
Abstract
This paper presents the results of a practical automatic three-dimensional matching project. It consists of two major parts.
The first part is related to the automatic three-dimensional matching project implemented for a digital close range photography test. The components of this test include two CCD cameras with a resolution of 758×580 Pixels set on a 70cm horizontal bar. These cameras are set at a distance of 3m from the object. A new type of signs which have been devised for identification and extraction of control points from photos have been set on an around the area under examination. A computer program was prepared for automatic identification and extraction of these signs by computer.
The program is able to create a three-dimensional spatial shape (a model) from two images with cover automatically. The practical method is based on the Bundle Block Adjustment.
The second test was carried out with the aim of working with digitalized aerial photos. These signs have been set in place of fiducial marks and at ground control points. This test is somehow different from the first test, because in this case the program must first carry out the internal justification and then the relative and absolute adjustments.
In general, this paper discusses a method which is used for achievement of automatic matching in digital photography.  
1- Forstner, W. and Gulch E., 1987. A fast operator for detection and precise Location of distinct points, corners and centers of circular features. ISPRS Intercommission Workshop, Interlaken, Switzerland, pp 281-305.
2- Forstner, W., 1986. A Feature based correspondence algorithm for image matching. Int. Arch. of Photogrammetry and Remote Sensing, Vol.26- 3/3, pp 150-166.
3- Fraser, C.S. and Shortis, M.R., 1984. Vision metrology in industrial inspection: A practical evaluation. Proceedings of the Commission V, Close Range Techniques and Machine Vision. Melbourne, Australia. PP 87-91.
4- Hahn, M. and Brenner, C. Area based matching of colour Swizerland. Pp 227-236.
5- Helava, U.V., 1988. On system concepts for digital automation. Photogrammetria. 43 pp 57-71.
6- Homainejad, A.S. and Shortis, M.R. Development of a template for automatic Stereo matching. 1995 ISPRS Intercommission Workshop. Zurich, Switzerland. Pp 318-322.
7- Lemmens, M., 1988. A survey on stereo matching techniques. Preceedings, Commission 5, 16 th Congress of the International Society for Photogrammety and Remote Sensing. Kyoto, Japan. Pp 11-23.
8- Moravec, H.P., 1977. Towards automatic Visual obstacle avoidance. Proceedings, 5th Int. Joint Conf. Arificial Intellignce, Cambridge, MA. P 584.
9-  Nasrabadi, N.M., 1992. A stereo vision technique using curve-segments and relaxation matching. IEEE Transaction on Pattern Analysis and Machine Intelligence, Vol. 14, No. 5,. Pp 566-572.
10- Sim, D.G., Ham, Y.K.  and Park, R.H., 1994. On-line recognition of cursive Korean characters using DP matching and fuzzy concept. Pattern Recognition, Vol.27, No.12.pp 1605-1620.
11- Skalet, G.D., Lee, G.Y.G., Lander, L.J., 1992. Implementation of softcopy photogrammetric workstation at the U.S Geological Survey. Photogrammetric Engineering & Remote Sensing. Pp 57-63.
12- Vollmerhaus, D. and Bildanalyse, K., 1987. A fast algorithm for local matching of patterns in images. Proceedings, Intercommission Conference on Fast Processing of Photogrammetric Data. Interlaken, Switzerland. Pp 273-280.
Scientific- Research Quarterly of Geographical Data (SEPEHR)
Volume 7, Issue 27
Autumn 1998
Pages 12-18