Abstract
In this paper we propose a methodology for semantic indexing of images, based on techniques of image segmentation, classification and fuzzy reasoning. The proposed knowledge-assisted analysis architecture integrates algorithms applied on three overlapping levels of semantic information: i) no semantics, i.e. segmentation based on low-level features such as color and shape, ii) mid-level semantics, such as concurrent image segmentation and object detection, region-based classification and, iii) rich semantics, i.e. fuzzy reasoning for extraction of implicit knowledge. In that way, we extract semantic description of raw multimedia content and use it for indexing and retrieval purposes, backed up by a fuzzy knowledge repository. We conducted several experiments to evaluate each technique, as well as the whole methodology in overall and, results show the potential of our approach.
This research was supported by the European Commission under contract FP6-027026 K-SPACE.
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Adamek, T., O’Connor, N., Murphy, N.: Region-based segmentation of images using syntactic visual features. In: Proc. Workshop on Image Analysis for Multimedia Interactive Services, WIAMIS 2005, Switzerland (April 2005)
Athanasiadis, T., Mylonas, P., Avrithis, Y., Kollias, S.: Semantic image segmentation and object labeling. IEEE Trans. on Circuits and Systems for Video Technology 17(3), 298–312 (2007)
Baader, F., McGuinness, D., Nardi, D., Patel-Schneider, P.F.: The Description Logic Handbook: Theory, implementation and applications. Cambridge University Press, Cambridge (2002)
Benmokhtar, R., Huet, B.: Neural network combining classifier based on dempster-shafer theory for semantic indexing in video content. In: International MultiMedia Modeling Conference, vol. 4351, pp. 196–205 (2007)
Chandramouli, K., Izquierdo, E.: Image classification using self organizing feature maps and particle swarm optimization. In: Proc. 7th International Workshop on Image Analysis for Multimedia Interactive Services, WIAMIS (2006)
Denoeux, T.: An evidence-theoretic neural network classifier. In: International Conference on Systems, Man and Cybernetics, vol. 3, pp. 712–717 (1995)
Klir, G.J., Yuan, B.: Fuzzy Sets and Fuzzy Logic: Theory and Applications. Prentice-Hall, Englewood Cliffs (1995)
Naphade, M., Huang, T.S.: A probabilistic framework for semantic video indexing, filtering and retrieval. IEEE Trans. on Multimedia 3(1), 144–151 (2001)
Pan, J.Z., Stamou, G., Stoilos, G., Thomas, E.: Expressive querying over fuzzy DL-Lite ontologies. In: Proceedings of the International Workshop on Description Logics (DL 2007) (2007)
Papadopoulos, G.T., Mezaris, V., Kompatsiaris, I., Strintzis, M.G.: Combining global and local information for knowledge-assisted image analysis and classification. EURASIP J. Adv. Signal Process 2007(2), 18 (2007)
Smeaton, A.F., Over, P., Kraaij, W.: Evaluation campaigns and trecvid. In: MIR 2006: Proceedings of the 8th ACM International Workshop on Multimedia Information Retrieval, pp. 321–330. ACM Press, New York (2006)
Snoek, C., Huurninkm, B., Hollink, L., de Rijke, M., Schreiber, G., Worring, M.: Adding semantics to detectors for video retrieval. IEEE Trans. on Multimedia 9(5), 144–151 (2007)
Stoilos, G., Stamou, G., Tzouvaras, V., Pan, J.Z., Horrocks, I.: Reasoning with very expressive fuzzy description logics. Journal of Artificial Intelligence Research 30(5), 273–320 (2007)
Straccia, U.: Reasoning within fuzzy description logics. Journal of Artificial Intelligence Research 14, 137–166 (2001)
Vapnik, V.: The Nature of Statistical Learning Theory. Springer, Heidelberg (2000)
Zhang, L., Lin, F., Zhang, B.: Support vector machine learning for image retrieval. In: International Conference on Image Processing, vol. 2 (2001)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2009 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Athanasiadis, T. et al. (2009). Integrating Image Segmentation and Classification for Fuzzy Knowledge-Based Multimedia Indexing. In: Huet, B., Smeaton, A., Mayer-Patel, K., Avrithis, Y. (eds) Advances in Multimedia Modeling . MMM 2009. Lecture Notes in Computer Science, vol 5371. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-92892-8_29
Download citation
DOI: https://doi.org/10.1007/978-3-540-92892-8_29
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-92891-1
Online ISBN: 978-3-540-92892-8
eBook Packages: Computer ScienceComputer Science (R0)