Margarita Torre 
  
  
Figure 6: Parcels obtained 60 % faster than when manually drawn and with sub-pixel accuracy. 
6 ACKNOWLEDGEMENTS 
This work was partly funded by a research grant from CICYT (Ref. TIC98-1100). 
REFERENCES 
(Barsky 87) R.H. Bartels, J.C. Beatty, B.A. Barsky. An Introduction to Splines for use in Computer Graphics and Geo- 
metric Modeling. Morgan Kaufmann Publishers, Los Altos, California,1987. 
(Cees 99) H.M. Cees, H. La Poutré, R.J. Mokken. Density-Based unsupervised classification for Remote Sensing. Machine 
Vision and Advanced Image Processing in Remote Sensing, Springer-Verlag Berlin. Heidelberg, 1999. 
(Chun 96) S. Chun, A. Yuille. Region Competition: Unifying Snakes, Region Growing, and Bayes/MDL for Multi-band 
Image Segmentation. IEEE Transactions on Pattern Analysis and Machine Intelligence. Vol. 18, n? 9, 1996. 
(Dellepiane 99) S. Dellepiane. Detail-Preserving of Remote Sensing Images. Machine Vision and Advanced Image Pro- 
cessing in Remote Sensing.Springer- Verlag Berlin. Heidelberg, 1999. 
(Gruen 97) A. Gruen, H. Li. Linear Feature Extraction with 3-D LSB-Snakes. Automatic extraction of Man-Made Objects 
from Aerial and Space Images(II).Pags 287-298. Birkhäuser 1997. 
(Gülch 97) E. Gulch. Application of Semi-Automatic Building Acquisition. Automatic extraction of Man-Made Objects 
from Aerial and Space Images(II). Pags 129-138. Birkhäuser 1997. 
(Hong 84) T.H. Hong, A. Rosenfeld. Compact Region Extraction using Weighted Pixel Linking in a Pyramid. IEEE 
Transactions on Pattern Analysis and Machine Intelligence Vol. 6, n° 2, 1984. 
  
International Archives of Photogrammetry and Remote Sensing. Vol. XXXIII, Part B3. Amsterdam 2000. 895