Unforced Image Partitioning by Weighted Pyramid Linking

Abstract

This paper describes a method of image segmentation that creates a partition of the image into compact, homogeneous regions using a parallel, iterative approach that does not require immediate forced choices. The approach makes use of a 'pyramid' of successively reduced-resolution versions of the image. It defines link strengths between pairs of pixels at successive levels of this pyramid, based on proximity and similarity, and iteratively recomputes the pixel values and adjusts the link strengths. After a few iterations, the link strengths stabilize, and the links that remain strong define a set of subtrees of the pyramid. Each such tree represents a compact (piece of a ) homogeneous region in the image; the leaves of the subtree are the pixels in the region, and the size of the region depends on how high the root of the tree lies in the pyramid. Thus the trees define a partition of the image into (pieces of) homogeneous regions.

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 1982
Accession Number
ADP000113

Entities

People

  • Azriel Rosenfeld
  • Tsai-hong Hong

Organizations

  • University of Maryland

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Algorithms
  • Applied Computer Science
  • Artificial Intelligence
  • Biological Sciences
  • Blood Cells
  • Classification
  • Computer Science
  • Computer Vision
  • Computing-Related Activities
  • Image Processing
  • Image Segmentation
  • Images
  • Infrared Images
  • Iterations
  • Night Vision
  • Recognition

Readers

  • Computational Linguistics
  • Electromagnetic Wave Scattering and Antenna Radiation Engineering
  • Operations Research