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Image Similarity – From Fuzzy Sets to Color Image Applications

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Advances in Visual Information Systems (VISUAL 2007)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 4781))

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Abstract

Image similarity is an important topic in the field of image processing. The goal is to obtain objective measures that express the similarity between two images in a way that matches human evaluation. Such measures have both theoretical and practical applications. In this paper, we show how similarity measures for fuzzy sets have been modified in order to be applied in image processing. We also discuss a new application of these measures in the context of color image retrieval, indicating the potential of this class of similarity measures.

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Authors and Affiliations

  1. Ghent University, Dept. of Applied Mathematics and Computer Science, Fuzziness and Uncertainty Modelling Research Unit, Krijgslaan 281 - S9, 9000 Gent, Belgium

    Mike Nachtegael, Stefan Schulte, Valerie De Witte, Tom Mélange & Etienne E. Kerre

Authors
  1. Mike Nachtegael
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  2. Stefan Schulte
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  3. Valerie De Witte
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  4. Tom Mélange
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  5. Etienne E. Kerre
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Editor information

Guoping Qiu Clement Leung Xiangyang Xue Robert Laurini

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© 2007 Springer-Verlag Berlin Heidelberg

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Nachtegael, M., Schulte, S., De Witte, V., Mélange, T., Kerre, E.E. (2007). Image Similarity – From Fuzzy Sets to Color Image Applications. In: Qiu, G., Leung, C., Xue, X., Laurini, R. (eds) Advances in Visual Information Systems. VISUAL 2007. Lecture Notes in Computer Science, vol 4781. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-76414-4_4

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  • DOI: https://doi.org/10.1007/978-3-540-76414-4_4

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-76413-7

  • Online ISBN: 978-3-540-76414-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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