Extended fractal analysis for texture classification and segmentation
- 1 January 1999
- journal article
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Transactions on Image Processing
- Vol. 8 (11), 1572-1585
- https://doi.org/10.1109/83.799885
Abstract
The Hurst parameter for two-dimensional (2-D) fractional Brownian motion (fBm) provides a single number that completely characterizes isotropic textured surfaces whose roughness is scale-invariant. Extended self-similar (ESS) processes were previously introduced in order to provide a generalization of fBm. These new processes are described by a number of multiscale Hurst parameters. In contrast to the single Hurst parameter, the extended parameters are able to characterize a greater variety of natural textures where the roughness of these textures is not necessarily scale-invariant. In this work, we evaluate the effectiveness of multiscale Hurst parameters as features for texture classification and segmentation. For texture classification, the performance of the generalized Hurst features is compared to traditional Hurst and Gabor features. Our experiments show that classification accuracy for the generalized Hurst and Gabor features are comparable even though the generalized Hurst features lower the dimensionality by a factor of five. Next, the segmentation accuracy using generalized and standard Hurst features is evaluated on images of texture mosaics. For these experiments, the performance is evaluated with and without supplemental contrast and average grayscale features. Finally, we investigate the effectiveness of the Hurst features to segment real synthetic aperture radar (SAR) imageryKeywords
This publication has 35 references indexed in Scilit:
- Fast image synthesis using an extended self-similar (ESS) modelPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2002
- Multiscale segmentation and anomaly enhancement of SAR imageryIEEE Transactions on Image Processing, 1997
- Periodicity, directionality, and randomness: Wold features for image modeling and retrievalIEEE Transactions on Pattern Analysis and Machine Intelligence, 1996
- Comparison of human performance with algorithms for estimating fractal dimension of fractional Brownian statisticsJournal of the Optical Society of America A, 1993
- The fractal properties of topography: A comparison of methodsEarth Surface Processes and Landforms, 1992
- Vector Quantization and Signal CompressionPublished by Springer Science and Business Media LLC ,1992
- Fractional Brownian Motion: A Maximum Likelihood Estimator and Its Application to Image TextureIEEE Transactions on Medical Imaging, 1986
- Fractal-Based Description of Natural ScenesIeee Transactions On Pattern Analysis and Machine Intelligence, 1984
- An Algorithm for Vector Quantizer DesignIEEE Transactions on Communications, 1980
- Fractional Brownian Motions, Fractional Noises and ApplicationsSIAM Review, 1968