Perceptually-Based Functions for Coarseness Textural Feature Representation

Authors:
J. Chamorro-Martínez;E. Galán-Perales;B. Prados-Suárez;J. M. Soto-Hidalgo
Affiliations:
Department of Computer Science and Artificial Intelligence, University of Granada, C/ Periodista Daniel Saucedo Aranda s/n, 18071 Granada, Spain;Department of Computer Science and Artificial Intelligence, University of Granada, C/ Periodista Daniel Saucedo Aranda s/n, 18071 Granada, Spain;Department of Computer Science, University of Jaén, C/ Alfonso X el Sabio s/n, 23700 Linares, Jaén, Spain;Department of Computer Science and Artificial Intelligence, University of Granada, C/ Periodista Daniel Saucedo Aranda s/n, 18071 Granada, Spain
Venue:
IbPRIA '07 Proceedings of the 3rd Iberian conference on Pattern Recognition and Image Analysis, Part I
Year:
2007

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Abstract

Coarseness is a very important textural concept that has been widely analyzed in computer vision for years. However, a model which allows to represent different perception degrees of this textural concept in the same way that humans perceive texture is needed. In this paper we propose a model that associates computational measures to human perception by learning an appropriate function. To do it, different measures representative of coarseness are chosen and subjects assessments are collected and aggregated. Finally, a function that relates these data is fitted.