Jalal Amini
Figure 6. Smooth of 5b
As it is seen in figure 6, manual edition of the skeleton to some limited extend, can help extract linear objects in
more efficient way.
6 CONCLUSIONS
Extraction of objects in aerial and satellite imagery is important in digital photogrammetry. There are many
different types of objects in aerial and space images such as roads, bridges, buildings and so on. That require
different algorithms for detecting objects of interest. In many applications, before the main process is started, it is
necessary to simplify the image which contain important objects for our application.
This paper shows images could be simplified by using mathematical morphology operators. The application of
structure element , ( ^ ) , on binary images, resulted in extraction of objects’ skeleton from images, In the next
step, the application of another structure element , ( p ^) , resulted in removing skeletal legs.
The application of mathematical morphological operation to spatial data processing in photogrammetry and
remote sensing can be considered as an extension of spatial analysis functions typical of GIS. The thinning
operation makes it possible for spatial data in raster form to be vectorized and put directly into a vector based
GIS. Smoothing operations can be performed on binary images to delete short skeleton legs and isolated pixels
(i.e., one or two end points of a longer line).
REFERENCES
Dong,P., 1996. Implementation of mathematical morphological operations for spatial data processing. Computers
& Geociences, vol.23, No.1.
Jang,B.K.,and Chin,R.T., 1990. Analysis of thinning algorithms using mathematical morphology. IEEE Trans.
Pattern analysis and machine intell., v.12, no.6, p.541-551.
Haralick,R.M., Sternberg,S.R.,and Zhuang X., 1987. Image analysis using mathematical morphology. IEEE
Trans.Pattern analysis and machine intell.,v.1 9, no.4, p.532-550.
Hahn,M., and Geiselmann,G.,1998. Identification of simple objects in image sequences.
Serra,J., 1982. Image analysis and mathematical morphology. Academic press, London,610p.
Steudel,A.,Glesner,M., 1996. Image coding with fuzzy region growing segmentation. IEEE Trans. Electronic
computers, p.955-962.
Wang,D.,Haese Coat, V.,Bruno,A.,and Ronsin,J.,1995. Some statistical properties of mathematical morphology.
IEEE Trans. signal processing , v.43, no.8, p.1955-1965.
42 International Archives of Photogrammetry and Remote Sensing. Vol. XXXIII, Part B3. Amsterdam 2000.
Sklans
in patt
