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In search of a new initialization of K-means clustering for color quantization

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

3 Citations (Scopus)

Abstract

Color quantization is still an important auxiliary operation in the processing of color images. The K-means clustering (KM), used to quantize the color, requires an appropriate initialization. In this paper, we propose a combined KM method that use to initialize the results of well-known quantization algorithms such as Wu's, NeuQuant (NQ) and Neural Gas (NG). This approach, assessed by three quality indices: PSNR, ΔE and ΔM, improves the results. Experimental results of such combined quantization indicate that the deterministic Wu+KM and random NG+KM approaches leading to the best quantized images.

Original languageEnglish
Title of host publicationEighth International Conference on Machine Vision, ICMV 2015
EditorsAntanas Verikas, Petia Radeva, Dmitry Nikolaev
PublisherSPIE
ISBN (Electronic)9781510601161
DOIs
Publication statusPublished - 2015
Event8th International Conference on Machine Vision, ICMV 2015 - Barcelona, Spain
Duration: 19 Nov 201521 Nov 2015

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume9875
ISSN (Print)0277-786X
ISSN (Electronic)1996-756X

Conference

Conference8th International Conference on Machine Vision, ICMV 2015
Country/TerritorySpain
CityBarcelona
Period19/11/1521/11/15

Keywords

  • Pixel clustering
  • color quantization
  • initialization
  • k-means
  • neural networks

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering

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