Imperfect pattern recognition using the fuzzy measure theory

Authors:
Anas Dahabiah;John Puentes;Basel Solaiman
Affiliations:
Image and Information Processing Department, TELECOM Bretagne, Technopôle Brest-Iroise, Brest Cedex 3, France;Image and Information Processing Department, TELECOM Bretagne, Technopôle Brest-Iroise, Brest Cedex 3, France;Image and Information Processing Department, TELECOM Bretagne, Technopôle Brest-Iroise, Brest Cedex 3, France
Venue:
IDEAL'09 Proceedings of the 10th international conference on Intelligent data engineering and automated learning
Year:
2009

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Abstract

This paper aims to provide a unified framework to deal with information imperfection and heterogeneity using possibility theory, in addition to information conflict and scarcity using Dempster-Shafer theory in order to classify imperfectly-described medical images. The proposed method is very robust and general. It can be applied without modification to any other database.