IAES International Journal of Artificial Intelligence (IJ-AI)
Vol 13, No 3: September 2024

Morphology for hexagonal image processing: a comprehensive simulation analysis

Cevik, Taner (Unknown)
Nematzadeh, Sajjad (Unknown)
Rasheed, Jawad (Unknown)
Alshammari, Abdulaziz (Unknown)



Article Info

Publish Date
01 Sep 2024

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.

Copyrights © 2024






Journal Info

Abbrev

IJAI

Publisher

Subject

Computer Science & IT Engineering

Description

IAES International Journal of Artificial Intelligence (IJ-AI) publishes articles in the field of artificial intelligence (AI). The scope covers all artificial intelligence area and its application in the following topics: neural networks; fuzzy logic; simulated biological evolution algorithms (like ...