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1 September 1993 Probabilistic approach to fractal-based texture discrimination
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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.
© (1993) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Jeffrey L. Solka, Carey E. Priebe, and George W. Rogers "Probabilistic approach to fractal-based texture discrimination", Proc. SPIE 1962, Adaptive and Learning Systems II, (1 September 1993); https://doi.org/10.1117/12.150589
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