DocumentCode
3307657
Title
A Comparison of Ridge Detection Methods for DEM Data
Author
Koka, Shinji ; Anada, Koichi ; Nakayama, Yasunori ; Sugita, Kimio ; Yaku, Takeo ; Yokoyama, Ryusuke
Author_Institution
Dept. Comput. Sci. & Syst. Anal., Nihon Univ., Narashino, Japan
fYear
2012
fDate
8-10 Aug. 2012
Firstpage
513
Lastpage
517
Abstract
We deal with ridge detection methods from digital elevation map (DEM) data. As ridge detection methods, the O (N2) -time steepest ascent method and the O (N) -time discrete Lap lace transform (D.L.T.) method are known, where N is the number of cells. However, the D.L.T. method is too blurry to form ridge lines. In this paper, we introduce a 12 neighbor D.L.T. method which is a modification of the 4 neighbor D.L.T. method. And we also introduce another ridge detection method by the classification of local shapes around each cell. We can consider 32 patterns for ridges or valleys. Furthermore, we compare and evaluate their ridge detection methods in a certain area. We note that our two methods provide blurry terrain maps, but it require only O (N) -time for N cells, in comparison with the steepest ascent method.
Keywords
Laplace transforms; digital elevation models; discrete transforms; feature extraction; image classification; object detection; terrain mapping; DEM data; DLT method; digital elevation map data; discrete Laplace transform; feature extraction; local shape classification; ridge detection methods; terrain maps; time steepest ascent method; Classification algorithms; Computer science; Educational institutions; Feature extraction; Laplace equations; NASA; Shape; digital elevation map (DEM) data; ridge detection; the steepest ascent method;
fLanguage
English
Publisher
ieee
Conference_Titel
Software Engineering, Artificial Intelligence, Networking and Parallel & Distributed Computing (SNPD), 2012 13th ACIS International Conference on
Conference_Location
Kyoto
Print_ISBN
978-1-4673-2120-4
Type
conf
DOI
10.1109/SNPD.2012.46
Filename
6299330
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