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Proceedings Paper

Fractal properties from 2D curvature on multiple scales
Author(s): Erhardt Barth; Christoph Zetzsche; Mario Ferraro; Ingo Rentschler
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Paper Abstract

Basic properties of 2-D-nonlinear scale-space representations of images are considered. First, local-energy filters are used to estimate the Hausdorff dimension, DH, of images. A new fractal dimension, DN, defined as a property of 2-D-curvature representations on multiple scales, is introduced as a natural extension of traditional fractal dimensions, and it is shown that the two types of fractal dimensions can give a less ambiguous description of fractal image structure. Since fractal analysis is just one (limited) aspect of scale-space analysis, some more general properties of curvature representations on multiple scales are considered. Simulations are used to analyze the stability of curvature maxima across scale and to illustrate that spurious resolution can be avoided by extracting 2-D-curvature features.

Paper Details

Date Published: 23 June 1993
PDF: 13 pages
Proc. SPIE 2031, Geometric Methods in Computer Vision II, (23 June 1993); doi: 10.1117/12.146648
Show Author Affiliations
Erhardt Barth, Institut fuer Medizinische Psychologie (Germany)
Christoph Zetzsche, Technische Univ. Muenchen (Germany)
Mario Ferraro, Univ. di Torino (Italy)
Ingo Rentschler, Institut fuer Medizinische Psychologie (Germany)

Published in SPIE Proceedings Vol. 2031:
Geometric Methods in Computer Vision II
Baba C. Vemuri, Editor(s)

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