Centroid Optimization

Centroid Optimization is a computational method in image quantization that iteratively refines the representative colors of clusters by minimizing the within-cluster distortion, typically through updating centroids to the mean of their assigned pixels in the color space.

208

Publications

9.8K

Citations

685

Authors

279

Institutions

Publications per year

2017–2026

86

Authors

685

  1. SN
    Shuryo Nakai

    University of British Columbia, Canada

    5 publications · 80 citations

    5

    h-index

  2. KN
    Kimio Nishimura

    Doshisha Women's College of Liberal Arts, Japan

    5 publications · 62 citations

    5

    h-index

  3. HS
    Hiroki Saeki

    Hokkaido University, Japan

    4 publications · 50 citations

    4

    h-index

  4. VG
    Vladimir G. Kim

    Adobe Systems (United States), United States

    2 publications · 625 citations

    2

    h-index

  5. DL
    Dzung L. Pham

    Johns Hopkins University, United States

    2 publications · 489 citations

    2

    h-index

1–5 of 685

Venues

  1. Pattern Recognition Letters

    6 publications · 929 citations

    6

    h-index

  2. Information Sciences

    5 publications · 663 citations

    5

    h-index

  3. Journal of Food Science

    JFS · 4 publications · 82 citations

    4

    h-index

  4. Food Science and Technology Research

    FSTR · 3 publications · 35 citations

    3

    h-index

  5. arXiv (Cornell University)

    Repository · 3 publications · 161 citations

    3

    h-index

1–5