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Image Classification by Web Images

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PRICAI 2002: Trends in Artificial Intelligence (PRICAI 2002)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 2417))

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Abstract

While main targets of conventional Web mining are numerical and textual data, we propose Web mining for image data. Thanks to the recent rapid spread of digital imaging devices, demand for generic image classification of various kinds of real world images becomes greater. Then, we propose generic image classification using a large number of images automatically gathered from the Web as learning images. As classification methods, we use image-feature-based search exploited in content-based image retrieval(CBIR), which do not restrict target images unlike conventional image recognition methods.

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References

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Author information

Authors and Affiliations

  1. Department of Computer Science, The University of Electro-Communications, 1-5-1 Chofugaoka, Chofu-shi, Tokyo, 182-8585, Japan

    Keiji Yanai

Authors
  1. Keiji Yanai
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Editor information

Editors and Affiliations

  1. School of Information Science and Technology Department of Information and Communication Engineering, University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-8656, Japan

    Mitsuru Ishizuka

  2. School of Information Technology Knowledge Representation and Reasoning Unit (KRRU) Faculty of Engineering and Information Technology, Griffith University, PMB 50 Gold Coast Mail Centre, Queensland, 9726, Australia

    Abdul Sattar

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© 2002 Springer-Verlag Berlin Heidelberg

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Yanai, K. (2002). Image Classification by Web Images. In: Ishizuka, M., Sattar, A. (eds) PRICAI 2002: Trends in Artificial Intelligence. PRICAI 2002. Lecture Notes in Computer Science(), vol 2417. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45683-X_83

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  • DOI: https://doi.org/10.1007/3-540-45683-X_83

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-44038-3

  • Online ISBN: 978-3-540-45683-4

  • eBook Packages: Springer Book Archive

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