Range Detection Of Strabismus Based On The Distance And Coordinates Of The Iris

Authors

  • Nur Syazlin Zolkiflia
  • Ain Nazari Department of Electronic Engineering, Faculty of Electrical and Electronic Engineering, Universiti Tun Hussein Onn Malaysia, Johor Malaysia
  • Rohaida Mat Akir Department of Electronic Engineering, Faculty of Electrical and Electronic Engineering, Universiti Tun Hussein Onn Malaysia, Johor Malaysia
  • Ashok Vajravelu Department of Electronic Engineering, Faculty of Electrical and Electronic Engineering, Universiti Tun Hussein Onn Malaysia, Johor Malaysia

Abstract

Strabismus is a failure of the two eyes to maintain a proper alignment with each other. It usually occurs because of the poor eye muscles control or on a very farsighted person. It also can occur in all stages of age. A timely diagnosis is required to prevent it from getting worse. However, the traditional screening method is done manually, require expertise, costly and timely. Thus, this research proposed a semi-automated range detection system based on the distance and coordinates of the iris. It can help to reduce the time for the ophthalmologist to diagnose the strabismus. This proposed system consists of three stages: (1) Pre-processing to remove noise and enhance the original image. (2) Locating the iris location (3) Classification into strabismus types. The sample images are taken from publicly online dataset: The Columbia Gaze dataset (CAVE) and Kaggle: Eye Disease dataset. It will be used as the input image for the system. By utilizing the image processing approach, this system will be able to assists the ophthalmology and health care practitioners as strabismus screening tools.

Downloads

Published

2022-12-31

How to Cite

Zolkiflia, N. S. ., Nazari, A. ., Akir, R. M. ., & Vajravelu, A. . (2022). Range Detection Of Strabismus Based On The Distance And Coordinates Of The Iris. International Journal of Advanced Computer Systems and Software Engineering, 2(1), 23–29. Retrieved from https://journal.scientiaca.org/index.php/ijacsse/article/view/29

Issue

Vol. 2 No. 1 (2021): January

Section

Articles