Title
New unsupervised hybrid classifier based on the fuzzy integral: applied to natural textured images
Abstract
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.
Year
DOI
Venue
2013
10.1049/iet-cvi.2011.0205
IET Computer Vision
Keywords
Field
DocType
decision trees,fuzzy set theory,image classification,image texture,natural scenes,unsupervised learning,fi,id3 strategy,aerial image,automatic parameter estimation,base supervised classifier,decision tree learning,fuzzy integral,general rule,natural textured image identification,unsupervised hybrid classifier
Computer vision,Margin (machine learning),Pattern recognition,Computer science,Fuzzy logic,Aerial image,Artificial intelligence,ID3,Margin classifier,Classifier (linguistics),Decision tree learning,Quadratic classifier
Journal
Volume
Issue
ISSN
7
4
1751-9632
Citations 
PageRank 
References 
2
0.52
6
Authors
5
Name
Order
Citations
PageRank
María Guijarro1495.79
ruben fuentesfernandez220.52
P. Javier Herrera3254.80
alejandro ribeiro420.52
Gonzalo Pajares569957.18