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Proceedings Paper

Segmentation and modeling of textured images through combined second- and third-order statistical models
Author(s): Tania Stathaki; Anthony G. Constantinides
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Paper Abstract

In this paper the problem of texture image analysis in the presence of noise is examined from a higher-order statistical perspective and in the context of noise. The objective is to develop analysis techniques through which robust texture characteristics are extracted and used for texture modelling and segmentation. The approaches taken involve the use of autoregressive models whose parameters derived first from joint and weighted second and third order cumulants and secondly as a solution to a weighted overdetermined set of equations in which the weights are appropriate functions of the eigenvalue spread. The required segmentation of such 2D random fields is effected through the additional stage of a neural network having as inputs the extracted autoregressive parameters. The paper describes the fundamental issues of the various components of the approach.

Paper Details

Date Published: 16 September 1994
PDF: 10 pages
Proc. SPIE 2308, Visual Communications and Image Processing '94, (16 September 1994); doi: 10.1117/12.185960
Show Author Affiliations
Tania Stathaki, Imperial College (United Kingdom)
Anthony G. Constantinides, Imperial College (United Kingdom)


Published in SPIE Proceedings Vol. 2308:
Visual Communications and Image Processing '94
Aggelos K. Katsaggelos, Editor(s)

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