Edge Detection of Flat Electroencephalography Image via Classical and Fuzzy Approach

  • Suzelawati Zenian
  • Tahir AhmadEmail author
  • Amidora Idris
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 652)


Edge detection is a crucial step in image processing in order to mark the point where the light intensity changed significantly. It is widely used to detect gray-scale and colour images in various fields such as medical image processing, machine vision system and remote sensing. The classical edge detectors such as Prewitt, Robert, and Sobel are quite sensitive towards noise and sometimes inaccurate. In this paper, the boundary of the epileptic foci of Flat EEG (fEEG) is determined by implementing some of the methods ranging from classical to fuzzy approach. There are two methods being applied for the fuzzy edge detector technique which are Minimum Constructor and Maximum Constructor methods; and Fuzzy Mathematical Morphology approach.


Flat EEG Fuzzy set Fuzzy image Grayscale morphology Edge detection Mathematical morphology 



The authors would like to thank their family members for their support and encouragement, the members of the Fuzzy Research Group (FRG), Department of Mathematics and Ibnu Sina Institute for Scientific and Industrial Research, UTM, and Universiti Malaysia Sabah (UMS) for their assistance and cooperation.


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Copyright information

© Springer Nature Singapore Pte Ltd. 2016

Authors and Affiliations

  • Suzelawati Zenian
    • 1
    • 3
  • Tahir Ahmad
    • 1
    • 2
    Email author
  • Amidora Idris
    • 1
  1. 1.Department of Mathematical Sciences, Faculty of ScienceUniversiti Teknologi MalaysiaUTM Johor BahruMalaysia
  2. 2.Centre for Sustainable Nanomaterials, Ibnu Sina Institute for Scientific and Industrial ResearchUniversiti Teknologi MalaysiaUTM Johor BahruMalaysia
  3. 3.Department of Mathematics with Computer Graphics, Faculty of Science and Natural ResourcesUniversiti Malaysia SabahKota KinabaluMalaysia

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