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International Conference on Hybrid Artificial Intelligence Systems

HAIS 2012: Hybrid Artificial Intelligent Systems pp 404–415Cite as

A Hybrid Gradient for n-Dimensional Images through Hyperspherical Coordinates

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 7209))

Abstract

We propose a hybrid gradient which provides a good behavior on regions with different illumination. It avoids the shadow effects focusing on the detection of regions of the scene with different chromatic properties. It works with image intensity and chromaticity according with its intensity level emulating the Human Vision System (HVS). This gradient is grounded in the Hyperspherical coordinates, therefore it has a general propose and can be applied on RGB images, multi-spectral images or hyperspectral images.

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Author information

Authors and Affiliations

  1. Computational Intelligence Group, University of the Basque Country, Spain

    Ramón Moreno & Manuel Graña

Authors
  1. Ramón Moreno
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  2. Manuel Graña
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Editor information

Editors and Affiliations

  1. Universidad de Salamanca, Plaza de la Merced S/N, 37008, Salamanca, Spain

    Emilio Corchado

  2. VŠB-TU Ostrava 17, Listopadu 15, 70833, Ostrava, Czech Republic

    Václav Snášel

  3. Machine Intelligence Research Labs Machine Intelligence Research Labs(MIR Labs),, Scientific Network for Innovation and Research Excellence, P.O. Box 2259, 98071, Auburn, Washington, USA

    Ajith Abraham

  4. Wroclaw University of Technology, Wybrzeze Wyspianskiego 27, 50-370, Wroclaw, Poland

    Michał Woźniak

  5. University of the Basque Country, Pº Manuel Lardizabal 1, 20018, San Sebastian, Spain

    Manuel Graña

  6. Yonsei University, 134 Shinchon-dong, 120-749, Sudaemoon-ku, Seoul, Korea

    Sung-Bae Cho

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© 2012 Springer-Verlag Berlin Heidelberg

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Moreno, R., Graña, M. (2012). A Hybrid Gradient for n-Dimensional Images through Hyperspherical Coordinates. In: Corchado, E., Snášel, V., Abraham, A., Woźniak, M., Graña, M., Cho, SB. (eds) Hybrid Artificial Intelligent Systems. HAIS 2012. Lecture Notes in Computer Science(), vol 7209. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-28931-6_39

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  • DOI: https://doi.org/10.1007/978-3-642-28931-6_39

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-28930-9

  • Online ISBN: 978-3-642-28931-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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