Share Email Print
cover

Proceedings Paper

Robust fractal characterization of 1D and 2D signals
Author(s): Niranjan Avadhanam; Sunanda Mitra
Format Member Price Non-Member Price
PDF $14.40 $18.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

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)

© SPIE. Terms of Use
Back to Top