Comparison of various improved-partition fuzzy c-means clustering algorithms in fast color reduction

Laszlo Szilagyi, Gellert Denesi, L. Kovács, Sandor M. Szilagyi

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

1 Citation (Scopus)

Abstract

This paper provides a comparative study of several enhanced versions of the fuzzy c-means clustering algorithm in an application of histogram-based image color reduction. A common preprocessing is performed before clustering, consisting of a preliminary color quantization, histogram extraction and selection of frequently occurring colors of the image. These selected colors will be clustered by tested c-means algorithms. Clustering is followed by another common step, which creates the output image. Besides conventional hard (HCM) and fuzzy c-means (FCM) clustering, the so-called generalized improved partition FCM algorithm, and several versions of the suppressed FCM (s-FCM) in its conventional and generalized form, are included in this study. Accuracy is measured as the average color difference between pixels of the input and output image, while efficiency is mostly characterized by the total runtime of the performed color reduction. Numerical evaluation found all enhanced FCM algorithms more accurate, and four out of seven enhanced algorithms faster than FCM. All tested algorithms can create reduced color images of acceptable quality.

Original languageEnglish
Title of host publicationSISY 2014 - IEEE 12th International Symposium on Intelligent Systems and Informatics, Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages197-202
Number of pages6
ISBN (Print)9781479959969
DOIs
Publication statusPublished - Oct 14 2014
Event12th IEEE International Symposium on Intelligent Systems and Informatics, SISY 2014 - Subotica, Serbia
Duration: Sep 11 2014Sep 13 2014

Other

Other12th IEEE International Symposium on Intelligent Systems and Informatics, SISY 2014
CountrySerbia
CitySubotica
Period9/11/149/13/14

Fingerprint

Clustering algorithms
Color
Pixels

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Artificial Intelligence

Cite this

Szilagyi, L., Denesi, G., Kovács, L., & Szilagyi, S. M. (2014). Comparison of various improved-partition fuzzy c-means clustering algorithms in fast color reduction. In SISY 2014 - IEEE 12th International Symposium on Intelligent Systems and Informatics, Proceedings (pp. 197-202). [6923585] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/SISY.2014.6923585

Comparison of various improved-partition fuzzy c-means clustering algorithms in fast color reduction. / Szilagyi, Laszlo; Denesi, Gellert; Kovács, L.; Szilagyi, Sandor M.

SISY 2014 - IEEE 12th International Symposium on Intelligent Systems and Informatics, Proceedings. Institute of Electrical and Electronics Engineers Inc., 2014. p. 197-202 6923585.

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

Szilagyi, L, Denesi, G, Kovács, L & Szilagyi, SM 2014, Comparison of various improved-partition fuzzy c-means clustering algorithms in fast color reduction. in SISY 2014 - IEEE 12th International Symposium on Intelligent Systems and Informatics, Proceedings., 6923585, Institute of Electrical and Electronics Engineers Inc., pp. 197-202, 12th IEEE International Symposium on Intelligent Systems and Informatics, SISY 2014, Subotica, Serbia, 9/11/14. https://doi.org/10.1109/SISY.2014.6923585
Szilagyi L, Denesi G, Kovács L, Szilagyi SM. Comparison of various improved-partition fuzzy c-means clustering algorithms in fast color reduction. In SISY 2014 - IEEE 12th International Symposium on Intelligent Systems and Informatics, Proceedings. Institute of Electrical and Electronics Engineers Inc. 2014. p. 197-202. 6923585 https://doi.org/10.1109/SISY.2014.6923585
Szilagyi, Laszlo ; Denesi, Gellert ; Kovács, L. ; Szilagyi, Sandor M. / Comparison of various improved-partition fuzzy c-means clustering algorithms in fast color reduction. SISY 2014 - IEEE 12th International Symposium on Intelligent Systems and Informatics, Proceedings. Institute of Electrical and Electronics Engineers Inc., 2014. pp. 197-202
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