Segmentation of images by expansion and contraction

  • Authors:
  • W. A. Perkins

  • Affiliations:
  • Computer Science Department, Research Laboratories, General Motors Corporation, Warren, Michigan

  • Venue:
  • IJCAI'79 Proceedings of the 6th international joint conference on Artificial intelligence - Volume 2
  • Year:
  • 1979

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Abstract

A new method for segmenting Images using edge points to separate regions of smoothly varying intensity is discussed. Region segmentation using edge points has not been very successful in the past because small gaps would allow merging of dissimilar regions. The present method uses an expansion-contraction technique in which the edge regions are expanded to close gaps and then contracted after the separate uniform regions have been identified. In order to perserve small uniform regions, the process is performed iteratively with increasing expansions, but no expansion for edge regions that already separate different regions. The final result is a set of uniform intensity regions (usually less than 100) and a set of edge boundary regions. The program has successfully segmented scenes with industrial parts, landscapes, and IC chips.