Flat EEG Image Segmentation by Fuzzy Entropy-Based Multi-Level Thresholding

Matematika

article

Suzelawati Zenian¹  Tahir Ahmad²  Norhafiza Hamzah¹ 

[1] Universiti Malaysia Sabah;Universiti Teknologi Malaysia

关键词: Flat EEG;    thresholding;    uncertainty;    fuzzy set;    entropy.;   

DOI  :  10.11113/matematika.v38.n2.1357

学科分类：社会科学、人文和艺术（综合）

来源: Universiti Teknologi Malaysia * Fakulti Sains

【 摘 要 】

Thresholding is a type of image segmentation that deals with the conversion of an image with many gray levels into another image with fewer gray levels. It classifies grayscale pixels into two categories which creates a binary image. However, the output image is not alwayssatisfying due to several factors such as inherent image vagueness as uncertainty arises within the gray values of an image. In this paper, a multi-level image thresholding based on fuzzy entropy is applied on Flat Electroencephalography (Flat EEG) image. The outcomes are compared visually with global thresholding.

【 授权许可】

Unknown