• DocumentCode
    1207572
  • Title

    Adaptive image region-growing

  • Author

    Chang, Yian-Leng ; Li, Xiaobo

  • Author_Institution
    Dept. of Comput. Sci., Alberta Univ., Edmonton, Alta., Canada
  • Volume
    3
  • Issue
    6
  • fYear
    1994
  • fDate
    11/1/1994 12:00:00 AM
  • Firstpage
    868
  • Lastpage
    872
  • Abstract
    Proposes a simple, yet general and powerful, region-growing framework for image segmentation. The region-growing process is guided by regional feature analysis; no parameter tuning or a priori knowledge about the image is required. To decide if two regions should be merged, instead of comparing the difference of region feature means with a predefined threshold, the authors adaptively assess region homogeneity from region feature distributions. This results in an algorithm that is robust with respect to various image characteristics. The merge criterion also minimizes the number of merge rejections and results in a fast region-growing process that is amenable to parallelization
  • Keywords
    adaptive signal processing; image segmentation; minimisation; adaptive image region-growing; image characteristics; merge criterion; minimization; parallelization; region feature distributions; region homogeneity; region-growing framework; regional feature analysis; Councils; Histograms; Image analysis; Image segmentation; Robustness; Testing;
  • fLanguage
    English
  • Journal_Title
    Image Processing, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1057-7149
  • Type

    jour

  • DOI
    10.1109/83.336259
  • Filename
    336259