Skip to main navigation Skip to search Skip to main content

Deterministic vs. random initializations for K-Means color image quantization

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

4 Citations (Scopus)

Abstract

We present six methods for initialising the K-means clustering algorithm used for color image quantization. We test these initialization methods on a few quantization levels and on 24 color images contained in the Kodak image dataset. In the vast majority of the examined cases the best results were obtained for the initialization of KM++. The evaluation of the results was carried out using the MSE and several new perceptual quality indices.

Original languageEnglish
Title of host publicationProceedings - 15th International Conference on Signal Image Technology and Internet Based Systems, SISITS 2019
EditorsKokou Yetongnon, Albert Dipanda, Gabriella Sanniti di Baja, Luigi Gallo, Richard Chbeir
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages50-55
Number of pages6
ISBN (Electronic)9781728156866
DOIs
Publication statusPublished - Nov 2019
Event15th International Conference on Signal Image Technology and Internet Based Systems, SISITS 2019 - Sorrento, Italy
Duration: 26 Nov 201929 Nov 2019

Publication series

NameProceedings - 15th International Conference on Signal Image Technology and Internet Based Systems, SISITS 2019

Conference

Conference15th International Conference on Signal Image Technology and Internet Based Systems, SISITS 2019
Country/TerritoryItaly
CitySorrento
Period26/11/1929/11/19

Keywords

  • Color image quantization
  • Image quality indices
  • Initialization
  • K means
  • K-means
  • Wu's algorithm

ASJC Scopus subject areas

  • Computer Science Applications
  • Signal Processing
  • Media Technology
  • Computer Networks and Communications

Fingerprint

Dive into the research topics of 'Deterministic vs. random initializations for K-Means color image quantization'. Together they form a unique fingerprint.

Cite this