DocumentCode
2008451
Title
A Combination of Positive and Negative Fuzzy Rules for Image Classification Problem
Author
Nguyen, Thanh Minh ; Wu, Q. M Jonathan
Author_Institution
Dept. of Electr. & Comput. Eng., Univ. of Windsor, Windsor, ON
fYear
2008
fDate
11-13 Dec. 2008
Firstpage
741
Lastpage
746
Abstract
In this paper, we propose a new fuzzy rule-based system for application in image classification problem. Each rule in our proposed system can represent more than one class. While traditional fuzzy systems consider positive fuzzy rules only, in this paper, we focus on combining negative fuzzy rules with traditional positive ones leading to fuzzy inference systems. This new approach has been tested on image classification problem consisting of multiple images with excellent results.
Keywords
fuzzy reasoning; fuzzy set theory; image classification; fuzzy inference systems; fuzzy rule-based system; image classification; negative fuzzy rules; positive fuzzy rules; Adaptive systems; Application software; Association rules; Data mining; Fuzzy sets; Fuzzy systems; Image classification; Knowledge based systems; Machine learning; Testing; Positive and negative rules; adaptive fuzzy system; image classification;
fLanguage
English
Publisher
ieee
Conference_Titel
Machine Learning and Applications, 2008. ICMLA '08. Seventh International Conference on
Conference_Location
San Diego, CA
Print_ISBN
978-0-7695-3495-4
Type
conf
DOI
10.1109/ICMLA.2008.14
Filename
4725058
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