A comparison of ridge detection methods for DEM data

Shinji Koka*, Koichi Anada, Yasunori Nakayama, Kimio Sugita, Takeo Yaku, Ryusuke Yokoyama

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Citations (Scopus)

Abstract

We deal with ridge detection methods from digital elevation map (DEM) data. As ridge detection methods, the O (N) -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.

Original languageEnglish
Title of host publicationProceedings - 13th ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing, SNPD 2012
Pages513-517
Number of pages5
DOIs
Publication statusPublished - 2012 Nov 12
Event13th ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing, SNPD 2012 - Kyoto, Japan
Duration: 2012 Aug 82012 Aug 10

Publication series

NameProceedings - 13th ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing, SNPD 2012

Conference

Conference13th ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing, SNPD 2012
Country/TerritoryJapan
CityKyoto
Period12/8/812/8/10

Keywords

  • digital elevation map (DEM) data
  • ridge detection
  • the steepest ascent method

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Networks and Communications
  • Software

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