Robust Fractal characterization of 1-D and 2-D signals

Niranjan Avadhanam, Sunanda Mitra

Research output: Contribution to journalConference article

1 Scopus citations

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 (MLE) 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.

Original languageEnglish
Pages (from-to)232-244
Number of pages13
JournalProceedings of SPIE - The International Society for Optical Engineering
Volume2032
DOIs
StatePublished - Oct 29 1993
EventNeural and Stochastic Methods in Image and Signal Processing II 1993 - San Diego, United States
Duration: Jul 11 1993Jul 16 1993

Fingerprint Dive into the research topics of 'Robust Fractal characterization of 1-D and 2-D signals'. Together they form a unique fingerprint.

  • Cite this