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Fusing MPEG-7 visual descriptors for image classification

Spyrou, Evaggelos and Le Borgne, Hervé and Mailis, Theofilos and Cooke, Eddie and Avrithis, Yannis and O'Connor, Noel E. (2005) Fusing MPEG-7 visual descriptors for image classification. In: ICANN 2005 - International Conference on Artificial Neural Networks, 11-15 September 2005, Warsaw, Poland. ISBN 978-3-540-28755-1

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Abstract

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 project1 and more specifically in a beach/urban scene classification problem.

Item Type:Conference or Workshop Item (Paper)
Event Type:Conference
Refereed:Yes
Additional Information:The original publication is available at www.springerlink.com
Subjects:Computer Science > Information retrieval
DCU Faculties and Centres:Research Initiatives and Centres > Centre for Digital Video Processing (CDVP)
Published in:Artificial Neural Networks: Formal Models and Their Applications - ICANN 2005. Lecture Notes in Computer Science 3697. Springer Berlin / Heidelberg. ISBN 978-3-540-28755-1
Publisher:Springer Berlin / Heidelberg
Official URL:http://dx.doi.org/10.1007/11550907_134
Use License:This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License
Funders:European Commission FP6-00176, Enterprise Ireland, EI FR/2005/56
ID Code:353
Deposited On:18 Mar 2008 by DORAS Administrator. Last Modified 06 May 2010 10:28

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