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RGB Color Histogram Feature based Image Classification: An Application of Rough Reasoning

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Proceedings of the First International Conference on Intelligent Human Computer Interaction

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Abstract

In this paper, we have proposed a novel rough set based image classification method which uses RGB color histogram as features to classify images of different themes. We have used the concept of discernibility to analyze RGB color values and finding optimum color intervals to discern images of different themes. We have shown how the set of optimum color intervals for training set of images can be used to construct a representative sieve for training set of images to classify new set of images. We have also proposed rough membership based formulation to classify new set of images using representative sieve. The outlines of the system has been implemented and presented along with some results on a set of new images of different themes.

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Author information

Authors and Affiliations

  1. Samsung India Software Center, Noida, India

    Shailendra Singh

Authors
  1. Shailendra Singh
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Editors and Affiliations

  1. Indian Institute of Information Technology, Allahabad, India

    U. S. Tiwary (Professor), Tanveer J. Siddiqui (Assistant Professor), M. Radhakrishna (Professor) & M. D. Tiwari (Director) (Professor),  (Assistant Professor),  (Professor) &  (Director)

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© 2009 Indian Institute of Information Technology, India

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Singh, S. (2009). RGB Color Histogram Feature based Image Classification: An Application of Rough Reasoning. In: Tiwary, U.S., Siddiqui, T.J., Radhakrishna, M., Tiwari, M.D. (eds) Proceedings of the First International Conference on Intelligent Human Computer Interaction. Springer, New Delhi. https://doi.org/10.1007/978-81-8489-203-1_8

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  • DOI: https://doi.org/10.1007/978-81-8489-203-1_8

  • Publisher Name: Springer, New Delhi

  • Print ISBN: 978-81-8489-404-2

  • Online ISBN: 978-81-8489-203-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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