NEIGHBORHOOD-BASED VISION SYSTEMS

  • Authors:

  • Christopher J. Henry;James F. Peters

  • Affiliations:

  • Department of Electrical and Computer Engineering, University of Manitoba, Canada;Department of Electrical and Computer Engineering, University of Manitoba, Canada

  • Venue:
  • Cybernetics and Systems
  • Year:
  • 2011

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Abstract

The problem considered here is how to find similarities between digital images useful in the design of cybernetic vision systems. The solution to this problem stems from recent neighborhood-based vision systems research. A neighborhood is viewed in the context of a covering of a visual space defined by a tolerance relation. Determination of neighborhoods and tolerance classes leads to a highly practical tolerance near-set approach in vision system design. The contribution of this article is threefold: an algorithm for finding tolerance classes, a new measure for quantifying the similarity between tolerance classes, and a practical application in the design of cybernetic vision systems.