Outdoor image classification using artificial immune recognition system (AIRS) with performance evaluation by fuzzy resource allocation mechanism

Authors:
Kemal Polat;Seral Şahan;Halife Kodaz;Salih Güneş
Affiliations:
Eng.-Arch. Fac. Electrical & Electronics Eng., Selcuk University, Konya, Turkey;Eng.-Arch. Fac. Electrical & Electronics Eng., Selcuk University, Konya, Turkey;Eng.-Arch. Fac. Computer Eng., Selcuk University, Konya, Turkey;Eng.-Arch. Fac. Electrical & Electronics Eng., Selcuk University, Konya, Turkey
Venue:
CAIP'05 Proceedings of the 11th international conference on Computer Analysis of Images and Patterns
Year:
2005

Citing 3
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Abstract

AIRS classification algorithm, which has an important place among classification algorithms in the field of Artificial Immune Systems, has showed an effective and intriguing performance on the problems it was applied. In this study, the resource allocation mechanism of AIRS was changed with a new one determined by Fuzzy-Logic rules. This system, named as Fuzzy-AIRS and AIRS were used as classifiers in the classification of outdoor images. The classification of outdoor dataset taken from UCI repository of machine learning databases was done using 10-fold cross validation method. Both versions of AIRS well performed over other systems reported in UCI website for corresponding dataset. Fuzzy-AIRS reached to the classification accuracy of 90.00 % in the applications whereas AIRS obtained 88.20 %. Besides, Fuzzy-AIRS gained one more advantage over AIRS by means of classification time. In the experiments, it was seen that the classification time in Fuzzy-AIRS was reduced by about 67% of AIRS for dataset. Fuzzy-AIRS classifier proved that it can be used as an effective classifier for image classification by reducing classification time as well as obtaining high classification accuracies.