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Proceedings Paper

Probabilistic approach to fractal-based texture discrimination
Author(s): Jeffrey L. Solka; Carey E. Priebe; George W. Rogers
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Paper Abstract

This paper studies the distribution of power law signatures for various texture types within a grayscale texture quilt. The fractal based features are extracted for the quilt using the covering method. Three features for the power law regression line are extracted. They are slope, y- intercept, and an F test statistic. The underlying distributions of these features are modeled using a nonparametric probability density estimation technique known as adaptive mixtures. These distribution models are then used to distinguish between the sixteen textures in the quilt.

Paper Details

Date Published: 1 September 1993
PDF: 10 pages
Proc. SPIE 1962, Adaptive and Learning Systems II, (1 September 1993); doi: 10.1117/12.150589
Show Author Affiliations
Jeffrey L. Solka, Naval Surface Warfare Ctr. (United States)
Carey E. Priebe, Naval Surface Warfare Ctr. (United States)
George W. Rogers, Naval Surface Warfare Ctr. (United States)

Published in SPIE Proceedings Vol. 1962:
Adaptive and Learning Systems II
Firooz A. Sadjadi, Editor(s)

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