Corrigenda and addenda: tolerance near sets and image correspondence

  • Authors:

  • James F. Peters

  • Affiliations:

  • Computational Intelligence Laboratory, Department of Electrical and Computer Engineering, University of Manitoba, Winnipeg, Manitoba R3T 5V6, Canada

  • Venue:
  • International Journal of Bio-Inspired Computation
  • Year:
  • 2010

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Abstract

This article introduces corrigenda and addenda for tolerance near sets and image correspondence (Peters, 2009). The principal problem considered in this article is how to solve the image correspondence problem using a bio-inspired approach in the study of representative spaces (inspired by J.H. Poincare's work during the 1890s) and tolerance spaces (introduced by E.C. Zeeman during the 1960s). One solution to this problem is to consider a tolerance space form of near sets that model human perception. Near sets are disjoint sets that resemble each other, especially resemblance defined within perceptual representative spaces (a.k.a., tolerance spaces). The contribution of this article is threefold. First, corrigenda and addenda for the original IJBIC article are presented. Second, similarities between digital images are viewed within the context of perceptual representative spaces introduced in this article. Third, an approach to quantifying the nearness of digital images is shown using the Henry-Peters nearness measure.