ul 2004 
of the 
(dure, 
ed by 
ritical 
d the 
using 
. The 
large 
an be 
ia for 
ching 
els in 
same 
each 
place. 
lidate 
best 
sis of 
near 
stics, 
ecific 
t the 
ecific 
nimal 
  
nary 
ure- 
ture- 
  
  
  
   
  
    
©Quickbird Original Image Copyright 2002, Digital Globe) 
Figure 8. A patch of the Quickbird image shows the result of 
image-and-map registration. Left: the original images. Right: 
the boundary lines of parcel are colored as yellow and the blue 
color lines denote wall features. 
The primitive result derived using the geometric-structure- 
matching technique for automatic registration of a sub-scene of 
Quickbird imagery and a cadastral map is as shown in Figure 7. 
The four bright polygons represent cadastral parcels. A patch 
of the satellite image over the test area is shown as in Fig. 8, 
with the wall feature (blue lines) and the corresponding 
boundary line (yellow lines). Further work on improving the 
automatic algorithm and the relevant evaluation on the results 
of the image-and-map registration is in progress. 
5. CONCLUSIONS 
The algorithm of the proposed GSM technique has been 
validated using the Quickbird image and the corresponding 
cadastral map. The boundary lines and polygons of cadastral 
parcels are used as the elements of geometric structure in the 
studied case. Automatic techniques have been developed to 
match image features and the corresponding vector data. An 
error model in the procedures of image-and-map matching has 
been proposed. The error model is required to implement the 
algorithm of image-and-map registration in order to achieve 
high level of automation. The error model provides a threshold 
for optimising the results of the proposed GSM technique. The 
experimental results show that the magnitude of the error on 
the order of 4.5m resulted from the image-and-map registration 
algorithm is possible, and those errors are comparable with the 
predicted ones (4.2m). It is possible to eliminate the 
requirements of manual intervention for registering images and 
maps, provided that accurate vector data and header data of 
satellite images are available. Further work on improving the 
automatic algorithm and the relevant evaluation on the results 
of the image-and-map registration is in progress. Potential 
applications of the proposed algorithm include providing 
ground control for fully automatic photogrammetry and 
updating data of spatial information systems. 
ACKNOWLEDGEMENTS 
The result presented in this paper is part of the work in the 
project NSC 92-2211-E-014-006 sponsored by the National 
Science Council, ROC. The satellite image presented in the 
paper is sponsored under the project NSC 91-2211-E-014- 
007. The authors are grateful to the Government of 
Taoyuan County, Taiwan, ROC, for providing a digital map 
of cadastral parcels. The authors are also in debt to 
Professor C.-C. Chang and his group and Dr. S.-A. Chen for 
giving help on GPS field work and computational 
adjustment for the GPS observations. 
REFERENCES 
Baltsavias, E.P., 2004. Digital ortho-images — a powerful 
tool for the extraction of spatial and geo-information. /SPRS 
J. of Photogrammetry & Remote Sensing, 51, pp.63-77. 
Chen, P.-H. and Dowman, I, 2000. Geocoding using 
stereo-generated DEMs and automatically generated GCPs. 
International Archives of Photogrammetry and Remote 
Sensing, Amsterdam, Netherlands, Vol.33, Part Bl, pp. 38- 
45. 
Chen, P.-H. and Dowman, Ll, 2001. A weighted least 
squares solution for space intersection of spaceborne stereo 
SAR data. /EEE Trans. on Geo-Science and Remote 
Sensing, GE-39(2), pp. 233-240. 
Dowman, L, 1998. Automating Image Registration and 
Absolute Orientation: — Solution and“ Problems. 
Photogrammetric Record, 16, pp. 5-18. 
Habib, A. and Kelley, D., 2001. Single-photo resection 
using the modified Hough Transformation. 
Photogrammetric Engineering & Remote Sensing, 67(8), pp. 
909-914. 
Heipke, C., Pakzad, K. and Straub, B.-M., 2000. Image 
Analysis for GIS Data Acquisition. Photogrammetric 
Record, 16(96), pp. 963-985. 
Morgado, A. and Dowman, L, 1997. A procedure for 
automatic absolute orientation using aerial photographs and 
a map. ISPRS J. of Photogrammetry & Remote Sensing, 
52(4), pp. 169-182. 
Shapiro, L.G. and Haralick, R.M., 1981. Structure 
description and inexact matching. /EEE Trans. on Pattern 
Analysis and Machine Intelligence, 3, pp. 504-519. 
Shapiro, L.G. and Stockman, G., 2001. Computer Vision. 
Prentice Hall, Inc., 580 pages. 
Sowmya, A. and Trinder, J., 2001. Modelling and 
representation issues in automated feature extraction from 
aerial and satellite images, ISPRS J. of Photogrammetry & 
Remote Sensing, 55, pp. 34-47. 
Wang Y., 1998. Principle and applications of structural 
image matching. ISPRS Journal of Photogrammetry & 
Remote Sensing, 53, pp. 154-165.