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All Journal IAES International Journal of Artificial Intelligence (IJ-AI)
Cevik, Taner
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Computer Science & IT Engineering

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Morphology for hexagonal image processing: a comprehensive simulation analysis Cevik, Taner; Nematzadeh, Sajjad; Rasheed, Jawad; Alshammari, Abdulaziz
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 13, No 3: September 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v13.i3.pp2574-2590

Abstract

Morphological operators for binary and grayscale images are commonly used to eliminate noise, recognize contours or specific structures, and arrange shapes in image processing for physiological modeling and biomechanics applications. Even though morphology has been substantially developed in square-pixelbased-image-processing (SIP), no effort has been made to construct morphological operators in hexagonal-pixel-based-image-processing (HIP) yet. In this paper, we transform basic SIP-domain-morphological operators such as dilation, erosion, closing, and opening into HIP-domain and compare their performance with their SIP counterparts. It is the first time to give the fundamental morphological operators in the HIP domain. The operators developed in this paper initiate the research about morphology in the HIP domain by successfully filling a significant gap by eliminating HIP’s lack of basic operators, thus capable of producing enhanced images for better analysis in anatomical models related to biology and medicine research fields.
Co-Authors Alshammari, Abdulaziz Nematzadeh, Sajjad Rasheed, Jawad