Piecewise Approximation of Pictures using Maximal Neighborhoods.

Abstract

Suppose that we are given a picture having approximately piecewise constant gray level. Each point P has a largest neighborhood N(P) that is entirely contained in one of the constant regions, and the set of maximal N(P)'s (i.e., N(P)'s not contained in other N(P)'s) constitutes an economical description of the picture, generalizing the Blum skeleton or medial axis transformation. The picture can be smoothed, without excessive blurring, by averaging over each N(P). By taking differences between pairs of touching maximal N(P)'s, the edges between the regions can be detected; since this edge detection scheme is not based on symmetrical detection operators, it is not handicapped when two adjacent regions differ greatly in size. (Author)

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Document Details

Document Type
Technical Report
Publication Date
May 01, 1976
Accession Number
ADA032746

Entities

People

  • Azriel Rosenfeld
  • Larry S. Davis
  • Narenda Ahuja

Organizations

  • University of Maryland

Tags

Communities of Interest

  • Biomedical
  • Ground and Sea Platforms

DTIC Thesaurus Topics

  • Air Force
  • Blood Cells
  • Cells
  • Change Detection
  • Computer Graphics
  • Computer Science
  • Computers
  • Detection
  • Detectors
  • Image Processing
  • Information Processing
  • Pattern Recognition
  • Recognition
  • Shape
  • Skeleton
  • Standards
  • Universities

Readers

  • Approximation Theory.
  • Computer Vision.
  • Graph Algorithms and Convex Optimization.