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Object Recognition by Permanence of Ratios Based Fusion and Gaussian Bayes Decision

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Knowledge-Based and Intelligent Information and Engineering Systems (KES 2009)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 5711))

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Abstract

Object recognition in digital image processing is the task of finding a particular object in an image. Although there are many pattern recognition methods developed for handling the problem of object recognition, it is still a challenging task in computer vision systems and image understanding. This paper presents a new model for object recognition using the concepts of Bayes classifier, fusion of probability measures, and the permanence of ratios.

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Author information

Authors and Affiliations

  1. ADFA School of Information Technology and Electrical Engineering, The University of New South Wales, Canberra, ACT 2600, Australia

    Tuan D. Pham

Authors
  1. Tuan D. Pham
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Editor information

Editors and Affiliations

  1. University of Chile, Republica 701, 8370439, Santiago, Chile

    Juan D. Velásquez  & Sebastián A. Ríos  & 

  2. University of Brighton, BN2 4GJ, Brighton, UK

    Robert J. Howlett

  3. University of South Australia, 5095, Mawson Lakes, SA, Australia

    Lakhmi C. Jain

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© 2009 Springer-Verlag Berlin Heidelberg

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Pham, T.D. (2009). Object Recognition by Permanence of Ratios Based Fusion and Gaussian Bayes Decision. In: Velásquez, J.D., Ríos, S.A., Howlett, R.J., Jain, L.C. (eds) Knowledge-Based and Intelligent Information and Engineering Systems. KES 2009. Lecture Notes in Computer Science(), vol 5711. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04595-0_19

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  • DOI: https://doi.org/10.1007/978-3-642-04595-0_19

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-04594-3

  • Online ISBN: 978-3-642-04595-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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