Graph-based Segmentation

Graph-Based Segmentation is an image segmentation method that represents an image as a graph structure, where pixels or regions correspond to nodes and their pairwise similarities define weighted edges, enabling partitioning through graph-theoretic algorithms to detect perceptually meaningful regions.

617

Publications

61.4K

Citations

1.8K

Authors

658

Institutions

Publications per year

2017–2026

147

Variants

Graph-theoretic Segmentation

Authors

1.8K

  1. MS
    Milan Sonka

    University of Iowa, United States

    14 publications · 1.4K citations

    13

    h-index

  2. AX
    Alexandre X. Falcão

    Universidade Estadual de Campinas (UNICAMP), Brazil

    13 publications · 962 citations

    13

    h-index

  3. PA
    Paulo A. V. Miranda

    Universidade Estadual de Campinas (UNICAMP), Brazil

    12 publications · 454 citations

    11

    h-index

  4. LG
    Leo Grady

    Siemens (United States), United States

    11 publications · 3.7K citations

    10

    h-index

  5. OL
    Olivier Lézoray

    GREYC, France

    8 publications · 329 citations

    8

    h-index

1–5 of 1.8K

Venues

  1. IEEE Transactions on Pattern Analysis and Machine Intelligence

    TPAMI · 24 publications · 23.5K citations

    22

    h-index

  2. Pattern Recognition

    21 publications · 1.5K citations

    20

    h-index

  3. 14

    h-index

  4. IEEE Transactions on Image Processing

    12 publications · 1.2K citations

    12

    h-index

  5. arXiv (Cornell University)

    Repository · 11 publications · 314 citations

    10

    h-index

1–5