Lim, C.H. and Chan, C.S. (2012) A fuzzy qualitative approach for scene classification. In: World Congress on Computational Intelligence , 10-15 June 2012, Brisbane, Australia.
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Abstract
Scene classification has been studied extensively in the recent past. Most of the state-of-the-art solutions assumed that scene classes are mutually exclusive. However, this is not true as a scene image may belongs to multiple classes and different people are tend to respond inconsistently even given a same scene image. In this paper, we propose a fuzzy qualitative approach to address this problem. That is, we first adopted the fuzzy quantity space to model the training data. Secondly, we present a novel weight function, w to train a fuzzy qualitative scene model in the fuzzy qualitative states. Finally, we introduce fuzzy qualitative partition to perform the scene classification. Empirical results using a standard data set and a comparison with K-nearest neighbour has shown the effectiveness and robustness of the proposed method.
Item Type: | Conference or Workshop Item (Paper) |
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Funders: | UNSPECIFIED |
Subjects: | T Technology > T Technology (General) |
Divisions: | Faculty of Computer Science & Information Technology |
Depositing User: | Mr. Mohd Samsul Ismail |
Date Deposited: | 22 Sep 2015 00:06 |
Last Modified: | 22 Sep 2015 00:06 |
URI: | http://eprints.um.edu.my/id/eprint/14091 |
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