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An Intelligent System for Aerial Image Retrieval and Classification

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Methods and Applications of Artificial Intelligence (SETN 2004)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3025))

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Abstract

Content based image retrieval is an active research area of pattern recognition. A new method of extracting global texture energy descriptors is proposed and it is combined with features describing the color aspect of texture, suitable for image retrieval. The same features are also used for image classification, by its semantic content. An exemplar fuzzy system for aerial image retrieval and classification is proposed. The fuzzy system calculates the degree that a class, such as sea, clouds, desert, forests and plantations, participates in the input image. Target applications include remote sensing, computer vision, forestry, fishery, agricultures, oceanography and weather forecasting.

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Author information

Authors and Affiliations

  1. Laboratory of Robotics and Automation, Section of Production Systems, Department of Production and Management Engineering, Democritus University of Thrace, Building of University’s Library, Kimmeria, GR-671 00, Xanthi, Greece

    Antonios Gasteratos

  2. Department of Electrical and Computer Engineering, Democritus University of Thrace, Laboratory of Electronics, Section of Electronics and Information Systems Technology, Vassilisis Sophias 12, GR-671 00, Xanthi, Greece

    Panagiotis Zafeiridis & Ioannis Andreadis

Authors
  1. Antonios Gasteratos
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  2. Panagiotis Zafeiridis
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  3. Ioannis Andreadis
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Editor information

Editors and Affiliations

  1. Info and Communication Systems Eng, Aegean University, 83200, Karlovassi, Samos, Greece

    George A. Vouros

  2. Department of Informatics, University of Piraeus, Piraeus, Greece

    Themistoklis Panayiotopoulos

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© 2004 Springer-Verlag Berlin Heidelberg

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Gasteratos, A., Zafeiridis, P., Andreadis, I. (2004). An Intelligent System for Aerial Image Retrieval and Classification. In: Vouros, G.A., Panayiotopoulos, T. (eds) Methods and Applications of Artificial Intelligence. SETN 2004. Lecture Notes in Computer Science(), vol 3025. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-24674-9_8

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  • DOI: https://doi.org/10.1007/978-3-540-24674-9_8

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-21937-8

  • Online ISBN: 978-3-540-24674-9

  • eBook Packages: Springer Book Archive

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