Byung-Uk Park 
  
  
-105.9842 -106.0182 -0.0168 0.0142 
105.9822 -105.9848 0.0168 -0.0142 
Variance of unit weight 
0.000968 
Standard deviation of parameters 
0.0000061652 
0.0000061658 
0.0283184623 
0.0000061652 
0.0000061658 
0.0283184623 
Table 4. Results of interior orientation 
  
  
  
  
  
  
  
  
  
  
  
5 CONCLUSION 
In this research we demonstrated that finding the position of fiducial mark using Hough transform and local 
dynamic thresholding algorithm is possible in the scanned digital imagery. We also successfully performed interior 
orientation with calibration data. 
REFERNENCES 
D.H. Ballard, 1981, Generalizing the Hough transform to detect arbitrary shapes, Pattern Rocognition 13(2), pp. 111- 
122. 
Duda, R.O., and Hart, P.E., 1972, Use of Hough transformation to detect lines and curves in pictures, Commu. ACM. 
March 15, pp. 11-15. 
Hough, P.V.C., 1962, Methods and means for recognizing complex patterns, U.S. Patent 3,069,654, Dec. 
Sohn, H.G., 1996, Boundary Detection Using Multisensor Imagery: Application to Ice Sheet Margin Detection, Ph.D. 
Dissertation, Ohio State University. 
Tzvi, D.B., and Sandler, M.B. ,1990, Combinatorial Hough Transform, Pattern Rocognition Letters, Vol. 11, No. 3, pp. 
167-174 
Xu, L., Oja, E., and Kultanen, P.,1990, A new curve detection method : Randomized Hough transform(RHT), Pattem 
Recognition Letters, Vol. 11, No. 5, pp. 331-338. 
  
696 International Archives of Photogrammetry and Remote Sensing. Vol. XXXIII, Part B3. Amsterdam 2000. 
KEY \ 
ABST 
Image 
large Ss 
line in 
matchi 
epipol: 
epipol: 
derive 
betwee 
numbe 
the fl: 
corres 
the resi 
1 IN] 
Image : 
can be 
extract 
both pc 
useful 
contrib 
related 
The air 
describ 
method 
2 PR 
Epipol: 
overlap 
point. ] 
conditi. 
Let the 
another 
the obj 
are def 
intersec