Data driven bandwidth for medoid shift algorithm

Research output: Chapter in Book/Conference paperConference paperpeer-review

1 Citation (Scopus)


Adaptive data driven bandwidth for medoidshift algorithm has been proposed in this work. The proposed method has made it possible to perform clustering on a variety of high resolution statistically different images. Experiments are performed on natural images as well as daily life images. The images have been chosen such that a comparison analysis between fixed sample point estimator k and adaptive k can be carried out in detail. The results show that a fixed value of k=10 is good for statistically compact images but gives undesirable results in dispersed images. Data driven bandwidth is proposed for each data point/ pixel as well as the complete data set/ image. Experimental results have shown our algorithm to be robust. Performance is evaluated on the basis of root mean square error for the quality of clusters.

Original languageEnglish
Title of host publicationComputational Science and Its Applications - ICCSA 2011
EditorsBeniamino Murgante, Osvaldo Gervasi, Andrés Iglesias, David Taniar, Bernady O. Apduhan
PublisherSpringer-Verlag London Ltd.
Number of pages13
ISBN (Electronic)9783642218873
ISBN (Print)9783642218866
Publication statusPublished - 2011
Externally publishedYes
Event2011 International Conference on Computational Science and Its Applications, ICCSA 2011 - Santander, Spain
Duration: 20 Jun 201123 Jun 2011

Publication series

NameLecture Notes in Computer Science
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference2011 International Conference on Computational Science and Its Applications, ICCSA 2011


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