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Performance analysis of fuzzy aggregation operations for combining classifiers for natural textures in images



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Cruz García, Jesús Manuel de la and Guijarro Mata-García, María and Pajares Martinsanz, Gonzalo and Herrera Caro, Pedro Javier (2011) Performance analysis of fuzzy aggregation operations for combining classifiers for natural textures in images. In Hybrid Artificial Intelligent Systems, part. II. Lecture Notes in Computer Science, 6679 . Springer-Verlag Berlín, pp. 180-188. ISBN 978-3-642-21221-5

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Official URL: http://link.springer.com/chapter/10.1007/978-3-642-21222-2_22



One objective for classifying pixels belonging to specific textures in natural images is to achieve the best performance in classification as possible. We propose a new unsupervised hybrid classifier. The base classifiers for hybridization are the Fuzzy Clustering and the parametric Bayesian, both supervised and selected by their well-tested performance, as reported in the literature. During the training phase we estimate the parameters of each classifier. During the decision phase we apply fuzzy aggregation operators for making the hybridization. The design of the unsupervised classifier from supervised base classifiers and the automatic computation of the final decision with fuzzy aggregation operations, make the main contributions of this paper.

Item Type:Book Section
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© Springer-Verlag Berlin Heidelberg 2011.
International Conference on Hybrid Artificial Intelligence Systems (HAIS 2011) (6th. May 23-25, 2011. Wroclaw, Polonia). Partial funding has also been received from DPI2009-14552-C02-01 project, supported by the Ministerio de Educación y Ciencia of Spain within the Plan Nacional de I+D+i.

Uncontrolled Keywords:Classifier Combination, Fuzzy Aggregation, Parametric Estimation, Fuzzy Clustering, Bayes Classifier
Subjects:Sciences > Computer science
ID Code:22539
Deposited On:12 Sep 2013 08:08
Last Modified:04 Mar 2015 10:07

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