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AFSS International Conference on Fuzzy Systems

AFSS 2002: Advances in Soft Computing — AFSS 2002 pp 360–366Cite as

Pictorial Indexes and Soft Image Distances

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 2275))

Abstract

Different classes of image-distance functions are often used in computer vision. Robust pictorial indexes can be also constructed based on distance criteria for image retrieval purposes. This paper introduces two new classes of entropic distances that are based on the concept of convex transformations. Their formal properties are studied and tested on real images. Experiments on the comparison of images and the matching of objects are presented. A comparison of image distances, here, is proposed and carried out with measures of closeness.

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References

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Author information

Authors and Affiliations

  1. DMA, Palermo University, 90123, Palermo, Italy

    Vito Di Gesú

  2. Indian Statistical Institute, Calcutta, India

    Sisir Roy

Authors
  1. Vito Di Gesú
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  2. Sisir Roy
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Editor information

Editors and Affiliations

  1. Electronics and Communication Sciences Unit, Indian Statistical Institute, 203 B.T. Road, 700108, Calcutta, India

    Nikhil R. Pal

  2. Brain Science Institute, RIKEN, 2-1 Hirosawa, Wako, Japan

    Michio Sugeno

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© 2002 Springer-Verlag Berlin Heidelberg

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Di Gesú, V., Roy, S. (2002). Pictorial Indexes and Soft Image Distances. In: Pal, N.R., Sugeno, M. (eds) Advances in Soft Computing — AFSS 2002. AFSS 2002. Lecture Notes in Computer Science(), vol 2275. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45631-7_48

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  • DOI: https://doi.org/10.1007/3-540-45631-7_48

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-43150-3

  • Online ISBN: 978-3-540-45631-5

  • eBook Packages: Springer Book Archive

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