Selecting the structuring element for morphological texture classification

Authors:
E. de Ves;X. Benavent;G. Ayala;J. Domingo
Affiliations:
Department of Informatics, University of Valencia, Valencia, Spain;Institute of Robotics, University of Valencia, Aptdo. de correos 2085, 46071, Valencia, Spain;Department of Statistics and Operation Research, University of Valencia, Aptdo. de correos 2085, 46071, Valencia, Spain;Institute of Robotics, University of Valencia, Aptdo. de correos 2085, 46071, Valencia, Spain
Venue:
Pattern Analysis & Applications
Year:
2006

Citing 0
Cited 3

A relevance feedback CBIR algorithm based on fuzzy sets

Image Communication
Combining similarity measures in content-based image retrieval

Pattern Recognition Letters
Automated human identification using ear imaging

Pattern Recognition

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper deals with a concrete aspect of texture classification: the choice of a good structuring element (SE) when the texture features used for classification are obtained from morphological granulometries. First, a granulometry is defined from the morphological opening of the texture using a convex and compact subset containing the origin as SE. Then, some usual distributional descriptors (mean, variance, skewness and kurtosis) of the granulometric size distribution are used as texture features. The main point of the paper is the choice of a good SE from the point of view of texture classification. A methodology is explained and software has been developed that helps in such a choice, for any given criterion for the quality of the classification.