On Combining Classifiers by Relaxation for Natural Textures in Images

Authors:
María Guijarro;Gonzalo Pajares;P. Javier Herrera
Affiliations:
Centro Superior de Estudios Felipe II. Ingeniería Técnica en Informática de Sistemas, Madrid, Spain 28300;Dpt. Ingeniería del Software e Inteligencia Artificial, Facultad Informática, Universidad Complutense, Madrid, Spain 28040;Dpt. Ingeniería del Software e Inteligencia Artificial, Facultad Informática, Universidad Complutense, Madrid, Spain 28040
Venue:
HAIS '08 Proceedings of the 3rd international workshop on Hybrid Artificial Intelligence Systems
Year:
2008

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Abstract

One objective for classifying textures in natural images is to achieve the best performance possible. As reported in the literature, the combination of classifiers performs better than simple ones. The problem is how they can be combined. We propose a relaxation approach, which combines two base classifiers, namely: the probabilistic Bayesian and the fuzzy clustering. The first establishes an initial classification, where the probability values are reinforced or punished by relaxation based on the support provided by the second. A comparative analysis is carried out against classical classifiers, verifying its performance.