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Proceedings Paper

Robust fractal characterization of 1D and 2D signals
Author(s): Niranjan Avadhanam; Sunanda Mitra
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Paper Abstract

Fractal characterization of signals is well suited in analysis of some time series data and in classification of natural shapes and textures. A maximum likelihood estimator is used to measure the parameter H which is directly related to the fractal dimension. The robustness of the estimator and the performance of the method are demonstrated on datasets generated using a variety of techniques. Finally the characterization is used in segmentation of composite images of natural textures.

Paper Details

Date Published: 29 October 1993
PDF: 13 pages
Proc. SPIE 2032, Neural and Stochastic Methods in Image and Signal Processing II, (29 October 1993); doi: 10.1117/12.162041
Show Author Affiliations
Niranjan Avadhanam, Texas Tech Univ. (United States)
Sunanda Mitra, Texas Tech Univ. (United States)

Published in SPIE Proceedings Vol. 2032:
Neural and Stochastic Methods in Image and Signal Processing II
Su-Shing Chen, Editor(s)

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