Full text: Proceedings, XXth congress (Part 8)

nbul 2004 International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XXXV, Part B-YF. Istanbul 2004 
When the obtained images are analyzed, the images are thought 
to reveal the expected line not clearly but at a beneficial degree. 
If the human intervention could be decreased to the least in this 
kind of research, could better results be reached? Developing a 
program that would decrease the human intervention to the least 
was targeted to be able to response of this question and our 
studies on this subject are going on. If a complete automation 
can be provided by using this type of program in the future, 
good results can be taken in different areas by doing this kind of 
In this research; on the selected example constructions, desired 
lines are tried to be determined by using derivative methods on 
traditional edge detection methods. The first point that must be 
careful at this method is the edges’ to be proved to slip from 
their places. Another point is, these methods are too sensible 
against noise. Its reason is that they define edges by the help of 
differences between two grey levels. At the original rock image 
that is utilized at the research, edges’ changing slowly and at a 
wide area, roughness of rock surface and noise effect cause 
edges’ to slip or not be fixed clearly. 
By the result of Sobel, Prewitt, Robert operators from 
derivative methods and LoG filter are practiced to the original 
image; when the obtained images are compared and the whole 
image is considered, Sobel operator was proved to be more 
effective in defining the lines; however, by Prewitt and Robert 
operators, the images that have similar features with the reasons 
sourcing from image's specific construction is proved to be 
obtained. Because of being too sensible against noise, in 
practical operations, especially ‘Laplasyan Method’ was not 
used; LoG filter was used as it introduced effective results by 
being utilized with filters; at the result images, edges could not 
be determined as expected level because of the causes 
explained below. 
In addition, at the fault line fixation some difficulties are 
confronted because of the other geomorphologic features. 
At these studies, edges were revealed partially by edge 
detection techniques and only the demanded lines could not be 
revealed completely. The next research can be an automation 
that confirms a suppression of other minor details by revealing 
the main lines clearly. The distinction of lines has always been 
done by commenting by eyes up to now (qualitative). 
Schenk, T., 1999. Digital Photogrammetry. Terra Science, 
Laurelville, Ohio, USA. 
Erdon, A., 1992. Edge detection methods in digital images. 
Msc. Thesis, ITU., Istanbul, Turkey. 
Penn B.S, Gordon A.J, and Wendlandt R.F., 1993. Using neural 
networks to locate edges and linear features in satellite images. 
Computers & Geosciences, 19: 1545-1565. 
Gupta, R.P., 2002. Remote Sensing Geology. Springer-Verlag, 

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