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Interclass Fuzzy Rule Generation for Road Scene Recognition from Colour Images

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Computer Analysis of Images and Patterns (CAIP 2001)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2124))

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Abstract

In many image classification problems the extent of usefulness of any variable for the purposes of discrimination apriori is unknown. This paper describes a unique fuzzy rule generation system developed to overcome this problem. By investigating interclass relationships very compact rule sets are produced with redundant variables removed. This approach to fuzzy system development is applied to two problems. The first is the classification of the Fisher Iris data [4] and the second is a road scene classification problem, based on features extracted from video images taken by a camera mounted in a motor vehicle.

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Author information

Authors and Affiliations

  1. Electronics and Mathematics, University of Luton, Park Square, Luton, LU1 3JU, Bedfordfordshire, England

    Malcolm Wilson

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  1. Malcolm Wilson
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Editors and Affiliations

  1. Faculty of Electronics and Information Technology Institute of Radioelectronics, Warsaw University of Technology, ul. Nowowiejska 15/19, 00-665, Warsaw, Poland

    Władysław Skarbek

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© 2001 Springer-Verlag Berlin Heidelberg

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Wilson, M. (2001). Interclass Fuzzy Rule Generation for Road Scene Recognition from Colour Images. In: Skarbek, W. (eds) Computer Analysis of Images and Patterns. CAIP 2001. Lecture Notes in Computer Science, vol 2124. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44692-3_83

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  • DOI: https://doi.org/10.1007/3-540-44692-3_83

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-42513-7

  • Online ISBN: 978-3-540-44692-7

  • eBook Packages: Springer Book Archive

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