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Full-Automatic High-Level Concept Extraction from Images Using Ontologies and Semantic Inference Rules

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The Semantic Web – ASWC 2006 (ASWC 2006)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 4185))

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Abstract

One of the big issues facing current content-based image retrieval is how to automatically extract the semantic information from images. In this paper, we propose an efficient method that automatically extracts the semantic information from images by using ontologies and the semantic inference rules. In our method, MPEG-7 visual descriptors are used to extract the visual features of image which are mapped to the semi-concept values. We also introduce the visual and animal ontology which are built to bridge the semantic gap. The visual ontology facilitates the mapping between visual features and semi-concept values, and allows the definition of relationships between the classes describing the visual features. The animal ontology representing the animal taxonomy can be exploited to identify the object in an image. We also propose the semantic inference rules that can be used to automatically extract high-level concepts from images by applying them to the visual and animal ontology. Finally, we discuss the limitations of the proposed method and the future work.

This work was supported by Korea Research Foundation Grant funded by Korea Government(MOEHRD, Basic Research Promotion Fund, KRF-2005-003-D00288).

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Author information

Authors and Affiliations

  1. Department of Computer Science and Engineering, Hanyang University, Ansan-si, Gyeongki-do, 426-791, South Korea

    Kyung-Wook Park & Dong-Ho Lee

Authors
  1. Kyung-Wook Park
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  2. Dong-Ho Lee
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Editors and Affiliations

  1. The Institute of Scientific and Industrial Research, Osaka University, 8-1 Mihogaoka, 567-0047, Ibaraki, Osaka, Japan

    Riichiro Mizoguchi

  2. Key Laboratory of Intelligent Information Processing, Institute of Computing Technology, Chinese Academy of Sciences, 100080, Beijing,  

    Zhongzhi Shi

  3. Information and Communication Technology, University of Trento, Italy

    Fausto Giunchiglia

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© 2006 Springer-Verlag Berlin Heidelberg

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Park, KW., Lee, DH. (2006). Full-Automatic High-Level Concept Extraction from Images Using Ontologies and Semantic Inference Rules. In: Mizoguchi, R., Shi, Z., Giunchiglia, F. (eds) The Semantic Web – ASWC 2006. ASWC 2006. Lecture Notes in Computer Science, vol 4185. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11836025_31

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  • DOI: https://doi.org/10.1007/11836025_31

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-38329-1

  • Online ISBN: 978-3-540-38331-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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