Open AccessFlat Electroencephalography Image: Image Size Dependent Normalization versus Fuzzy Technique
Author(s) -
Suzelawati Zenian,
Tahir Ahmad,
Amidora Idris
Publication year - 2019
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1358/1/012059
Subject(s) - normalization (sociology) , electroencephalography , grayscale , artificial intelligence , computer vision , computer science , pattern recognition (psychology) , fuzzy logic , image (mathematics) , contrast (vision) , image contrast , mathematics , psychology , neuroscience , sociology , anthropology
Flat Electroencephalography (fEEG) is a method for mapping high dimensional signal, namely Electroencephalography (EEG) into a low dimensional space. The image of fEEG which is in grayscale form is obtained from digital fEEG by using fuzzy approach. The main aim of this paper is to reduce the spread of the vague boundary and improve the visibility of the clusters of epileptic foci in terms of contrast enhancement via Image Size Dependent Normalization (ISDN) and fuzzy technique. Contrast performance comparison between both methods are carried out for an epileptic patient at varied time, t . It shows that fuzzy method gives better contrast compared to ISDN.