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Contrast Comparison of Flat Electroencephalography Image: Classical, Fuzzy, and Intuitionistic Fuzzy Set

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Soft Computing in Data Science (SCDS 2015)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 545))

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Abstract

Image processing is used to enhance visual appearance of images for further interpretation. One of the applications of image processing is in medical imaging. Generally, the pixel values of an image may not be precise as uncertainty arises within the gray values of an image due to several factors. In this paper, the image of Flat EEG (fEEG) is compared via classical, fuzzy, and intuitionistic fuzzy set (IFS) methods. Furthermore, the comparison between the input and output images of fEEG is carried out based on contrast comparison.

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Author information

Authors and Affiliations

  1. Department of Mathematical Sciences, Faculty of Science, Universiti Teknologi Malaysia, 81310 UTM, Johor Bahru, Malaysia

    Suzelawati Zenian & Amidora Idris

  2. Centre for Sustainable Nanomaterials, Ibnu Sina Institute for Scientific, and Industrial Research, Universiti Teknologi Malaysia, 81310 UTM, Johor Bahru, Malaysia

    Tahir Ahmad

Authors
  1. Suzelawati Zenian
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  2. Tahir Ahmad
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  3. Amidora Idris
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Corresponding author

Correspondence to Suzelawati Zenian .

Editor information

Editors and Affiliations

  1. University of Tennessee, Knoxville, Tennessee, USA

    Michael W. Berry

  2. Universiti Teknologi MARA, Shah Alam, Malaysia

    Azlinah Mohamed

  3. Universiti Teknologi MARA, Shah Alam, Malaysia

    Bee Wah Yap

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© 2015 Springer Science+Business Media Singapore

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Zenian, S., Ahmad, T., Idris, A. (2015). Contrast Comparison of Flat Electroencephalography Image: Classical, Fuzzy, and Intuitionistic Fuzzy Set. In: Berry, M., Mohamed, A., Yap, B. (eds) Soft Computing in Data Science. SCDS 2015. Communications in Computer and Information Science, vol 545. Springer, Singapore. https://doi.org/10.1007/978-981-287-936-3_10

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  • DOI: https://doi.org/10.1007/978-981-287-936-3_10

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-287-935-6

  • Online ISBN: 978-981-287-936-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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