Next Article in Journal
Robust and Accurate Algorithm for Wearable Stereoscopic Augmented Reality with Three Indistinguishable Markers
Previous Article in Journal
Monitoring and Analyzing of Circadian and Ultradian Locomotor Activity Based on Raspberry-Pi
Article Menu

Export Article

Open AccessArticle
Electronics 2016, 5(3), 57; doi:10.3390/electronics5030057

A Robust Automated Cataract Detection Algorithm Using Diagnostic Opinion Based Parameter Thresholding for Telemedicine Application

Department of Electronics and Communication Engineering, Motilal Nehru National Institute of Technology Allahabad 211004, India
*
Author to whom correspondence should be addressed.
Academic Editor: Mostafa Bassiouni
Received: 29 June 2016 / Revised: 2 August 2016 / Accepted: 6 September 2016 / Published: 15 September 2016
View Full-Text   |   Download PDF [3128 KB, uploaded 15 September 2016]   |  

Abstract

This paper proposes and evaluates an algorithm to automatically detect the cataracts from color images in adult human subjects. Currently, methods available for cataract detection are based on the use of either fundus camera or Digital Single-Lens Reflex (DSLR) camera; both are very expensive. The main motive behind this work is to develop an inexpensive, robust and convenient algorithm which in conjugation with suitable devices will be able to diagnose the presence of cataract from the true color images of an eye. An algorithm is proposed for cataract screening based on texture features: uniformity, intensity and standard deviation. These features are first computed and mapped with diagnostic opinion by the eye expert to define the basic threshold of screening system and later tested on real subjects in an eye clinic. Finally, a tele-ophthamology model using our proposed system has been suggested, which confirms the telemedicine application of the proposed system. View Full-Text
Keywords: pupil; cataract; texture information; K-Means clustering; graphic user interface (GUI); MATLAB; telemedicine pupil; cataract; texture information; K-Means clustering; graphic user interface (GUI); MATLAB; telemedicine
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

Pathak, S.; Kumar, B. A Robust Automated Cataract Detection Algorithm Using Diagnostic Opinion Based Parameter Thresholding for Telemedicine Application. Electronics 2016, 5, 57.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Electronics EISSN 2079-9292 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top