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Soft Computing in Image Processing pp 187–207Cite as

Fuzzy Image Segmentation Based on Triangular Function and Its n-dimensional Extension

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Part of the book series: Studies in Fuzziness and Soft Computing ((STUDFUZZ,volume 210))

Abstract

This chapter presents new fuzzy cluster algorithms within the image segmentation procedure. Firstly, we present the alternative algorithm for a onedimensional real space. This algorithm is based on triangular function. Secondly, the fuzzy clustering algorithms for the n-dimensional real space and the angular value set are presented, using an extension of the triangular function. We also explain the usage of these algorithms for gray level and color image segmentation. The color image segmentation is applied to the RGB space and to subspaces of an orthonormal color space called IJK.

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Author information

Authors and Affiliations

  1. Department of Informatics Technology, Tarom Company Calea Bucurestilor, Otopeni, jud. Ilfov, 224F, Romania

    Vasile Pătraşcu

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  1. Vasile Pătraşcu
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Editors and Affiliations

  1. Department of Applied Mathematics and Computer Science, Ghent University, Krijgslaan 281 – S9, Gent, 9000, Belgium

    Mike Nachtegael , Dietrich Van der Weken  & Etienne E. Kerre ,  & 

  2. Department of Telecommunications and Information Processing, Ghent University, Sint-Pietersnieuwstraat 41, Gent, 9000, Belgium

    Wilfried Philips

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Pătraşcu, V. (2007). Fuzzy Image Segmentation Based on Triangular Function and Its n-dimensional Extension. In: Nachtegael, M., Van der Weken, D., Kerre, E.E., Philips, W. (eds) Soft Computing in Image Processing. Studies in Fuzziness and Soft Computing, vol 210. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-38233-1_7

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  • DOI: https://doi.org/10.1007/978-3-540-38233-1_7

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-38232-4

  • Online ISBN: 978-3-540-38233-1

  • eBook Packages: EngineeringEngineering (R0)

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