International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XXXV, Part B5. Istanbul 2004 
  
   
  
  
   
    
  
  
  
  
  
  
  
            
  
      
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Figure 8. 3D features extracted for the left door of Al-Khasneh, the inner edge of the column is added from image based 
measurements. 
3.3 Image Segmentation 
The segmentation process is used to automatically extract the 
2D coordinates of the linear features from three different digital 
images. For this purpose, an edge detection based on the Lanser 
filler has been applied on the 3 imagery images. The third 
dimension of the segmented outlines is provided from the 
distance images. Figure 8, depicts the final 3D features 
extracted for the left door of Al-Khasneh. It can be seen that the 
data contains all of the edges and linear surface features in a 
clearly outlines. In total the feature-based representation 
contains 143.6 thousand points, whereas the original point 
cloud of the same portion has 1.1 million points. 
3.4 Occluded Features from Image Based Measurement 
It can be seen from the 3D features presented in figure 5 that 
due to the position of the laser scanner, the inner edge of the 
right column of the door has no data. The occluded edge can be 
added based on semiautomatic evaluation of digital imagery to 
have a complete data set for the scene. In our approach, the 3D 
coordinates of initial points were extracted manually. Then an 
automatic stereo matching has been applied for closely spaced 
images to add more points on the edge. For matching within the 
segmented parts of the edge epipolar constraint is used. The 
occluded edge is added to the 3D features as it can be shown in 
right part of figure 8. 
4. SUMMARY AND CONCLUSION 
The work described in this paper was developed as a part of an 
ongoing project, which aims to underline the necessity to 
integrate image based measurements and laser scanner 
    
techniques in order to optimize the geometric accuracy and the 
visual quality of 3D data capture for historical scenes. In our 
approach, the segmentation process is used as an intermediate 
step to extract information on edges and linear surface features, 
whereas the 3D information of theses details is provided from 
the laser scanner data. By the combination of both data sources, 
the shape of 3D features can be determined accurately, since the 
interpretation of point clouds and meshed models is improved 
using the available images. Finally, the approach applies semi- 
automated image based feature extraction. These features can be 
added to data from laser scanning in order to generate a more 
realistic perception of the complete scene. 
5. ACKNOWLEDGEMENTS 
Special thanks to the Hashemite University of Jordan and Petra 
Region Authority for support during the data collection. 
6. REFERENCES 
Boehler, W., Marbs, A., 2002. 3D scanning instruments. 
ISPRS/CIPA International Workshop on Scanning for Cultural 
Heritage Recording, Corfu, Greece, pp.9-12. 
Debevec, E., 1996. Modelling and Rendering Architecture from 
Photographs. Ph.D. Thesis, University of California at 
Berkeley. 
    
  
  
  
   
     
  
   
  
  
   
  
   
   
  
  
   
   
  
  
   
   
   
   
  
   
   
  
  
  
   
   
  
  
  
   
  
  
  
   
   
  
     
  
  
     
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