| E. Spyrou, H. LeBorgne, T. Mailis, E. Cooke, Y. Avrithis, N. O'Connor |
| Fusing MPEG-7 visual descriptors for image classiffication |
| W.Duch, J.Kacprzyk, E.Oja, and S.Zadrozny(Eds.), Artificial Neural Networks,Part II: Formal Models and their Applications, Springer, Vol. 3697, 2005, pp 847-852 |
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ABSTRACT
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| This paper proposes three content-based image classification techniques based on fusing various low-level MPEG-7 visual descriptors. Fusion is necessary as descriptors would be otherwise incompatible and inappropriate to directly include e.g. in a Euclidean distance. Three approaches are described: A "merging" fusion combined with an SVM classifier, a back-propagation fusion combined with a KNN classifier and a Fuzzy-ART neurofuzzy network. In the latter case, fuzzy rules can be extracted in an effort to bridge the "semantic gap" between the low-level descriptors and the high-level semantics of an image. All networks were evaluated using content from the repository of the aceMedia project and more specifically in a beach/urban scene classification problem.
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| 20 September, 2005 |
| E. Spyrou, H. LeBorgne, T. Mailis, E. Cooke, Y. Avrithis, N. O'Connor, "Fusing MPEG-7 visual descriptors for image classiffication", W.Duch, J.Kacprzyk, E.Oja, and S.Zadrozny(Eds.), Artificial Neural Networks,Part II: Formal Models and their Applications, Springer, Vol. 3697, 2005, pp 847-852 |
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