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19 August 1997 Segmentation of natural microtextures by joining local and global fractal model parameters
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Abstract
This paper deals with the problematic of the segmentation of natural images based on the fractal models. These models are based on the concept of measure of random sets and its self- similarity, and lead to the estimation of a single parameter for a natural texture: its fractal dimension. Different approaches to the implementation of the fractal geometry to the texture study are described and their properties stressed in order to obtain a close relationship between the humans point of view and the estimated fractal variables: the fractal dimension and the fractal density. The Hausdorff geometry of the measure in connection with the fractional Brownian model allowed to correlate the fractal dimension with the short range values of the autocorrelation function of properly transformed natural images, and the local definition of fractal dimensions of natural surfaces. The box counting and the covering blanket methods and algorithms were implemented and applied to estimate the fractal dimension, the lacunarity and the fractal signature of images of paper sheet and cork agglomerate surfaces. Results were statistically validated using the Kolmogorov-Smirnoff test statistics.
© (1997) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Antonio F. Limas Serafim "Segmentation of natural microtextures by joining local and global fractal model parameters", Proc. SPIE 3101, New Image Processing Techniques and Applications: Algorithms, Methods, and Components II, (19 August 1997); https://doi.org/10.1117/12.281299
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