1 September 1993 Probabilistic approach to fractal-based texture discrimination
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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, Jeffrey L. Solka, Carey E. Priebe, Carey E. Priebe, George W. Rogers, George W. Rogers, } "Probabilistic approach to fractal-based texture discrimination", Proc. SPIE 1962, Adaptive and Learning Systems II, (1 September 1993); doi: 10.1117/12.150589; https://doi.org/10.1117/12.150589


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