Automatic image segmentation by integrating color-edge extraction and seeded region growing

Jianping Fan, David K.Y. Yau, Ahmed K. Elmagarmid, Walid G. Aref

Research output: Contribution to journalArticle

440 Citations (Scopus)


We propose a new automatic image segmentation method. Color edges in an image are first obtained automatically by combining an improved isotropic edge detector and a fast entropic thresholding technique. After the obtained color edges have provided the major geometric structures in an image, the centroids between these adjacent edge regions are taken as the initial seeds for seeded region growing (SRG). These seeds are then replaced by the centroids of the generated homogeneous image regions by incorporating the required additional pixels step by step. Moreover, the results of color-edge extraction and SRG are integrated to provide homogeneous image regions with accurate and closed boundaries. We also discuss the application of our image segmentation method to automatic face detection. Furthermore, semantic human objects are generated by a seeded region aggregation procedure which takes the detected faces as object seeds.

Original languageEnglish
Pages (from-to)1454-1466
Number of pages13
JournalIEEE Transactions on Image Processing
Issue number10
Publication statusPublished - 1 Oct 2001



  • Edge detection
  • Face detection
  • Image segmentation
  • Seeded region growing (SRG)

ASJC Scopus subject areas

  • Software
  • Computer Graphics and Computer-Aided Design

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