Similarity hashing: A computer vision solution to the inverse problem of linear fractals

John C. Hart, Wayne O. Cochran, Patrick J. Flynn

Research output: Contribution to journalArticle

Abstract

The difficult task of finding a fractal representation of an input shape is called the inverse problem of fractal geometry. Previous attempts at solving this problem have applied techniques from numerical minimization, heuristic search and image compression. The most appropriate domain from which to attack this problem is not numerical analysis nor signal processing, but model-based computer vision. Self-similar objects cause an existing computer vision algorithm called geometric hashing to malfunction. Similarity hashing capitalizes on this observation to not only detect a shape's morphological self-similarity but also find the parameters of its self-transformations.

Original languageEnglish (US)
Pages (from-to)39-50
Number of pages12
JournalFractals
Volume5
Issue numberSUPPL. 1
StatePublished - Apr 1 1997
Externally publishedYes

Fingerprint

Hashing
Inverse problems
Fractals
Computer Vision
Computer vision
Fractal
Inverse Problem
Geometric Algorithms
Fractal Geometry
Heuristic Search
Image Compression
Self-similarity
Image compression
Signal Processing
Numerical analysis
Numerical Analysis
Signal processing
Attack
Model-based
Geometry

ASJC Scopus subject areas

  • Modeling and Simulation
  • Geometry and Topology
  • Applied Mathematics

Cite this

Similarity hashing : A computer vision solution to the inverse problem of linear fractals. / Hart, John C.; Cochran, Wayne O.; Flynn, Patrick J.

In: Fractals, Vol. 5, No. SUPPL. 1, 01.04.1997, p. 39-50.

Research output: Contribution to journalArticle

Hart, JC, Cochran, WO & Flynn, PJ 1997, 'Similarity hashing: A computer vision solution to the inverse problem of linear fractals', Fractals, vol. 5, no. SUPPL. 1, pp. 39-50.
Hart, John C. ; Cochran, Wayne O. ; Flynn, Patrick J. / Similarity hashing : A computer vision solution to the inverse problem of linear fractals. In: Fractals. 1997 ; Vol. 5, No. SUPPL. 1. pp. 39-50.
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