Title :
Image segmentation method based on self-organizing maps and K-means algorithm
Author :
Dragan M. Ristic;Milan Pavlovic;Irini Reljin
Author_Institution :
Faculty of Electrical Engineering, University of Belgrade, Bulevar Kralja Aleksandra 73, 11000, Serbia
Abstract :
In this paper, a method for color image segmentation based on Kohonenpsilas neural networks and clusterization by using modification of k-means algorithm, is presented. The method consists of three steps. First step includes usage of self-organizing maps for determination of potential candidates for regions centers. Secondly, using maxmin algorithm, number of candidates is reduced to initializing number of centers, which are then used for further analysis. During this process, initial number of regions is formed. For every formed region spatial and intensity centers are determined. Finally, in the third step, iterative procedure of modified k-means algorithm is realized during which the number of regions is minimized. The experimental results verify the usability of described algorithm.
Keywords :
"Image segmentation","Self organizing feature maps","Iterative algorithms","Neural networks","Clustering algorithms","Pixel","Color","Information retrieval","Data mining","Algorithm design and analysis"
Conference_Titel :
Neural Network Applications in Electrical Engineering, 2008. NEUREL 2008. 9th Symposium on
Print_ISBN :
978-1-4244-2903-5
DOI :
10.1109/NEUREL.2008.4685551
