Open AccessNew unsupervised hybrid classifier based on the fuzzy integral: applied to natural textured images
Author(s) -
Guijarro María,
FuentesFernández Rubén,
Herrera P. Javier,
Ribeiro Ángela,
Pajares Gonzalo
Publication year - 2013
Publication title -
iet computer vision
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.38
H-Index - 37
eISSN - 1751-9640
pISSN - 1751-9632
DOI - 10.1049/iet-cvi.2011.0205
Subject(s) - artificial intelligence , pattern recognition (psychology) , classifier (uml) , computer science , decision tree , fuzzy logic , fuzzy rule , machine learning , fuzzy set
This study presents a new unsupervised hybrid classifier for natural texture identification in aerial images. The proposed strategy combines through the fuzzy integral (FI) six well‐tested base supervised classifiers. This automation is based on the generation of a general rule inferred through decision tree learning, ID3 strategy from the training data. This rule allows generation of a partition of the set of images that the base classifiers use to estimate automatically their parameters. These parameters are the inputs to calculate the relative importance of each classifier in their combination by the FI. The resulting classifier has been compared with related techniques getting an improvement of 8.04% average. The study includes discussion on this comparison.