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

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.

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Publication Details

Journal
Pena Journal of Computer Science and Informatics
Published
2025-03-20
DOI
https://doi.org/10.37934/pjcsi.1.1.2531
Primary Topic
Advanced Computing and Algorithms
Type
article
Field-Weighted Citation Impact
0.00

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article

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

Suzelawati Zenian, Muhammad Abdy
1 links
Pena Journal of Computer Science and Informatics
Advanced Computing and Algorithms
article

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

Suzelawati Zenian, Muhammad Abdy
article en

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.

Pena Journal of Computer Science and InformaticsVol. 1(1)
Universiti of Malaysia Sabah (MY), State University of Makassar (ID)
Universiti Malaysia Sabah
Openalex Percentile: Top 89%
Advanced Computing and Algorithms
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Contrast Enhancement Technique for Flat EEG Image using Interval-Valued Type-II Fuzzy Sets — Suzelawati Zenian, Muhammad Abdy · Pena Journal of Computer Science and Informatics (2025) | TGRS Research Map | TGRS