Contrast Enhancement Technique for Flat EEG Image using Interval-Valued Type-II Fuzzy Sets

Authors

  • Suzelawati Zenian Mathematics Visualization (MathViz) Research Group, Faculty of Science and Natural Resources, Universiti Malaysia Sabah, Jalan UMS, 88400 Kota Kinabalu, Sabah, Malaysia
  • Muhammad Abdy Department of Mathematics, Universitas Negeri Makassar, Indonesia

Keywords:

EEG, structural similarity index, fuzzy set theory, image processing

Abstract

This paper presents a novel contrast enhancement technique specifically designed for flat EEG image. It aims to visualize the path of brainstorm that occur during seizure by reducing the spread of electrical potential in the cluster centres. The proposed approach involves the conversion of images into interval-valued fuzzy representations, followed by enhancement using the type-II fuzzy approach. The experimental results reveal that the integration of interval-valued and type-II techniques yields superior results compared to employing the interval-valued technique independently. Performance analysis, such as the structural similarity index measure (SSIM), demonstrates that the proposed method outperforms the non-combination approach.

Author Biographies

Suzelawati Zenian, Mathematics Visualization (MathViz) Research Group, Faculty of Science and Natural Resources, Universiti Malaysia Sabah, Jalan UMS, 88400 Kota Kinabalu, Sabah, Malaysia

suzela@ums.edu.my

Muhammad Abdy, Department of Mathematics, Universitas Negeri Makassar, Indonesia

muh.abdy@unm.ac.id

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Published

2025-03-20

Issue

Section

Articles