Abstract
One of the big issues facing current content-based image retrieval is how to automatically extract the high-level concepts from images. In this paper, we present an efficient system that automatically extracts the high-level concepts from images by using ontologies and semantic inference rules. In our method, MPEG-7 visual descriptors are used to extract the visual features of image, and the visual features are mapped to semi-concepts via the mapping algorithm. We also build the visual and animal ontologies to bridge the semantic gap. The visual ontology allows the definition of relationships among the classes describing the visual features and has the values of semi-concepts as the property values. The animal ontology can be exploited to identify the high-level concept in an image. Also, the semantic inference rules are applied to the ontologies to extract the high-level concept. Finally, we evaluate the proposed system using the image data set including various animal objects and discuss the limitations of our system.
Keywords
This work was supported by Korea Research Foundation Grant funded by the Korea Government(MOEHRD) (KRF-2006-521-D00457).
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References
Mackay, W.E.: EVA: An experimental video annotator for symbolic analysis of video data. SIGCHI Bulletin 21, 68–71 (1989)
Oomoto, E., Tanaka, K.: OVID: Design and Implementation of a Video-Object Database System. IEEE Trans. On Knowledge and Data Engineering 5, 629–643 (1993)
Smith, J.R., Chang, S.-F.: VisualSEEK: a fully automated content-based image query system. In: ACM Multimedia 96 (1996)
Carson, C., Thomas, M., Belongie, S., Hellerstein, J.M., Malik, J.: Blobworld: A System for Region-Based Image Indexing and Retrieval. In: Third International Conference on Visual Information Systems (1999)
Schreiber, A.T., Dubbeldam, B., Wielemaker, J., Wielinga, B.J.: Ontology-based photo annotation. In: IEEE Intelligent Systems, pp. 66–74 (2001)
Zhu, X., Fan, J., Elmagarmid, A.K., Wu, X.: Hierarchical video content description and summarization using unified semantic and visual similarity. Multimedia Syst. 9(1), 31–53 (2003)
Mezaris, V., Kompatsiaris, I., Strintz, M.G.: Region-based Image Retrieval using an Object Ontology and Relevance Feedback. EURASIP JASP (2004)
Jacob, M., Blu, T., Unser, M.: Efficient energies and algorithms for parametric snakes. IEEE Transactions on Image Processing 13, 1231–1244 (2004)
ISO/IEC 15938-5 FDIS Information Technology: MPEG-7 Multimedia Content Description Interface - Part 5: Multimedia Descriptin Schemes (2001)
Spyrou, E., Le Borgne, H., Mailis, T., Cooke, E., Avrithis, Y., O’Connor, N.E.: Fusing MPEG-7 Visual Descriptors for Image Classification. In: Duch, W., Kacprzyk, J., Oja, E., Zadrożny, S. (eds.) ICANN 2005. LNCS, vol. 3697, pp. 847–852. Springer, Heidelberg (2005)
Manjunath, B.S., Salembier, P., Sikora, T.: Introduction to MPEG-7 (2002)
Park, D.K., Jeon, Y.S., Won, C.S., Park, S.-J.: Efficient use of local edge histogram descriptor. In: ACM International Workshop on Standards, Interoperability and Practices, Marina del Rey, California, USA, pp. 52–54 (2000)
Hewlett-Packard: Jena Semantic Web Framework (2003), http://jena.sourceforge.net/
UMBC: F-OWL: An OWL Inference Engine in Flora-2, http://fowl.sourceforge.net
Jang, M., Sohn, J.-C.: Bossam: An Extended Rule Engine for OWL Inferencing. In: Antoniou, G., Boley, H. (eds.) RuleML 2004. LNCS, vol. 3323, pp. 128–138. Springer, Heidelberg (2004)
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Park, KW., Jeong, JW., Lee, DH. (2007). OLYBIA: Ontology-Based Automatic Image Annotation System Using Semantic Inference Rules. In: Kotagiri, R., Krishna, P.R., Mohania, M., Nantajeewarawat, E. (eds) Advances in Databases: Concepts, Systems and Applications. DASFAA 2007. Lecture Notes in Computer Science, vol 4443. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-71703-4_42
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DOI: https://doi.org/10.1007/978-3-540-71703-4_42
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