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Proceedings Paper

Multispectral edge detection using the two-dimensional self-organizing map
Author(s): Pekka J. Toivanen; Jarkko Ansamaki; S. Leppajarvi; Jussi P. S. Parkkinen
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Paper Abstract

In this paper ,a new method for edge detection in multispectral imags is presented. It is based on the use of the Self-Organizing Map (SOM), Peano scan and a conventional edge detector. The method presented in this paper order the vectors of the original image in such a way that vectors that are near each other according to some similarity criterium have scalar ordering values near each other. This is achieved using a 2D self-organizing map and the Peano scan. After ordering, the original vector image reduces to a gray-value image, and a conventional edge detector can be applied. In this paper, the Laplace and the Canny edge detectors are used. It is shown, that using the proposed method sit is possible to find the same relevant edges that R-ordering based methods find. Furthermore, it is also possible to find edges in images which consist of metameric colors, i.e. images in which every pixel vector maps into the same location in RGB space. This is not possible using conventional edge detectors which use an RGB image as input. Finally, the new method is tested with a real-world airplane image, giving results comparable with R-ordering based methods.

Paper Details

Date Published: 9 March 1999
PDF: 8 pages
Proc. SPIE 3647, Applications of Artificial Neural Networks in Image Processing IV, (9 March 1999); doi: 10.1117/12.341110
Show Author Affiliations
Pekka J. Toivanen, Lappeenranta Univ. of Technology (Finland)
Jarkko Ansamaki, Lappeenranta Univ. of Technology (Finland)
S. Leppajarvi, Lappeenranta Univ. of Technology (Finland)
Jussi P. S. Parkkinen, Lappeenranta Univ. of Technology (Finland)

Published in SPIE Proceedings Vol. 3647:
Applications of Artificial Neural Networks in Image Processing IV
Nasser M. Nasrabadi; Aggelos K. Katsaggelos, Editor(s)

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