Multiseeded Segmentation Using Fuzzy Connectedness

  • Authors:
  • Gabor T. Herman;Bruno M. Carvalho

  • Affiliations:
  • Temple Univ., Philadelphia, PA;Temple Univ., Philadelphia, PA, Univ. of Pennsylvania, Philadelphia

  • Venue:
  • IEEE Transactions on Pattern Analysis and Machine Intelligence
  • Year:
  • 2001

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Abstract

Fuzzy connectedness has been effectively used to segment out an object in a badly corrupted image. We generalize the approach by providing a definition which is shown to always determine a simultaneous segmentation of multiple objects. For any set of seed points, the segmentation is uniquely determined by the definition. An algorithm for finding this segmentation is presented and its output is illustrated. The algorithm is fast as compared to other segmentation algorithms in current use. We also report on an evaluation of the accuracy and robustness of the algorithm based on experiments in which several users were repeatedly asked to identify the seed points for the algorithm in a number of images.