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and stored together with the label in a database. Expert 
system technique is introduced during the detection of 
buildings with these descriptor values. After rules are 
generated and tested and accuracy of interpretation 
evaluated, ground coordinates of features of detected 
buildings are computed and projected to an existing Geo- 
Spatial Information System vector map. 
2. THE DETECTION PROCESS 
The detection process to automate the identification of 
building changes is designed as follows. 
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
Scan Aerial Photos Design 
(Stereo Pair) Descriptors 
: Using data 
i from 
; Existing 
Image Segmentation Geo-Spatial 
i Database 
and 
Extract Corner Extracted 
Points Points 
| | 
Transform Extracted Form 
Points to Ground Rulebase 
Coordinates 
Identify Buildings Produce Digital 
with Point Symbols Orthophotos 
Overlay and 
Display Result 
  
  
  
Aerial photos taken at a scale of about 1/3,000 are used 
as base material for interpretation. The films are then 
scanned and image segmentation is carried out with the 
scanned images to segment into regions and also labeled. 
Coordinates of corner points of segmented regions are 
transformed to object space. To test if the labeled regions 
are buildings, expert system is introduced. Descriptors of 
989 
regions are formulated to be used in the generation of a 
rulebase which will decide if the selected region is a 
building or not. A symbol will be generated at the 
centroid of the region and placed to represent the 
identified buildings. 
The symbols of detected buildings is again superimposed 
over the scene so that the user can visually confirm the 
result of the identified building. Buildings vector 
polygons with a symbol inside the polygon, will be 
buildings that are unchanged between the production of 
the vector maps and the exposure of the aerial photos. 
Newly built buildings will be those symbols that do not 
have an enclosing building vector polygon, and building 
vector polygons without a symbol inside will those that 
have been removed. Digital orthophotos are produced 
and displayed onto the screen. Vector maps of the same 
area, produced prior to the exposure of the aerial 
photographs, are superimposed over digital orthophotos 
as well as the point symbols representing detected 
buildings. 
3. APPLICATION OF IMAGE PROCESSING 
Image segmentation is the process of generating uniform 
and homogeneous areas for feature extraction. There are 
many different methods to segment digital images such 
as local line detection method, edge detection method, 
region growing method. Although many researches are 
being made to improve the quality of segmentation, 
many methods are of the ad hoc type leaving the user 
with no information about the quality of the result and 
the segmentation is not performed under the restriction 
of an object model requirements (Stokes, 1992.). Region 
growing method such as blob coloring is commonly used. 
The algorithm is described as using an L-shaped window 
mask to scan an image (Ballard and Brown, 1982.). The 
rows are examined by rows to check for differences in 
gray levels and if the difference is beyond a set value 
International Archives of Photogrammetry and Remote Sensing. Vol. XXXI, Part B4. Vienna 1996