IRMA-International.org: Creator of Knowledge
Information Resources Management Association
Advancing the Concepts & Practices of Information Resources Management in Modern Organizations

Human Health Diagnosis System Based on Iris Features

Human Health Diagnosis System Based on Iris Features
View Sample PDF
Author(s): Poonguzhali N (Pondicherry Engineering College, India), M. Ezhilarasan (Pondicherry Engineering College, India), R. Hariharan (Pondicherry Engineering College, India)and N. Praveen Devaraajan (Pondicherry Engineering College, India)
Copyright: 2018
Pages: 24
Source title: Computer Vision: Concepts, Methodologies, Tools, and Applications
Source Author(s)/Editor(s): Information Resources Management Association (USA)
DOI: 10.4018/978-1-5225-5204-8.ch037

Purchase

View Human Health Diagnosis System Based on Iris Features on the publisher's website for pricing and purchasing information.

Abstract

Iris feature has been used in authentication systems in many real time applications and is proved to provide high accuracy. Apart from authentication iris features can also be used for detecting pathological changes in human body and diagnose human health. The present study analyses the relationship between human iris anatomy and their health, as it is proved that changes in human health condition reflects the iris. Basically, in authentication system iris texture features are used for identification, in the proposed work iris texture and geometric features can also be deployed in diagnosing human health. The texture features present in the human iris are extracted using the mathematical statistical measure which is used to specify the characteristics of the texture of an image using gray-level co-occurrence matrix. The iris and pupil are extracted and correlated to the compactness features of the circle. Based on the comparison the system enables in prediction of abnormalities in the iris texture and identifies the affected person.

Related Content

Jayashri Dutta, Smitakshi Medhi, Mayurakshi Gogoi, Lisha Borgohain, Nourhan Gamal Abdel Maboud, Hanaa Mustafa Muhameed. © 2025. 34 pages.
Abdellah Khouz, Jorge Trindade, Fatima El Bchari, Pedro Pinto Santos, Eusébio Reis, Adil Moumane, Fatima Ezzahra El Ghazali, Mourad Jadoud, Blaid Bougadir. © 2025. 38 pages.
Phyo Thandar Hlaing, Muhammad Waqas, Usa Wannasingha Humphries. © 2025. 32 pages.
Adil Moumane, Jamal Al Karkouri, Batchi Mouhcine. © 2025. 28 pages.
Abdessamad Elmotawakkil, Nourddine Enneya. © 2025. 20 pages.
Fatima Ezzahra El Ghazali, Abdellah Khouz. © 2025. 30 pages.
Tarik Bahouq, Amina Moumane, Nadia Touhami. © 2025. 28 pages.
Body Bottom