NDLI: Image segmentation method based on self-organizing maps and K-means algorithm

Content Provider	IEEE Xplore Digital Library
Author	Ristic, D.M. Pavlovic, M. Reljin, I.
Copyright Year	2008
Description	Author affiliation: Fac. of Electr. Eng., Univ. of Belgrade, Belgrade (Ristic, D.M.; Reljin, I.) \|\| ICT Coll., Belgrade (Pavlovic, M.)
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.
Starting Page	27
Ending Page	30
File Size	5271872
Page Count	4
File Format	PDF
ISBN	9781424429035
DOI	10.1109/NEUREL.2008.4685551
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-09-25
Publisher Place	Serbia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Image segmentation Self organizing feature maps Iterative algorithms Neural networks Clustering algorithms Pixel Color Information retrieval Data mining Algorithm design and analysis K-means algorithm Color image segmentation Kohonen neural network self-organizing map
Content Type	Text
Resource Type	Article

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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