Title: Optimised retina verification system for pathological retina

Authors: B.M.S. Rani; A. Jhansi Rani

Addresses: ECE Department, Acharya Nagarajuna University, Guntur, AP, India ' ECE Department, V.R. Siddhartha Engineering College, Vijayawada, AP, India

Abstract: In retinal biometrics acknowledgment rate is influenced by the vasculature unpredictability of retinal pictures. Vascular example turns out to be extremely unpredictable in effected retinal images because of pathological signs. In this paper retina verification, which includes an AWN classifier to detect blood vessel structure from pathological retina. Distinct retinal feature which remains constant under pathological changes is bifurcation angle. This paper demonstrates a method for extraction of bifurcation angle. The particular bifurcation focuses had been created and positions are ascertained of a similar bifurcation indication. Sparse matrix representation used for retina template storing for optimisation of memory and the template is compared.

Keywords: retinal biometrics; vascular; AWN classifier; bifurcation angle; retina template; sparse matrix.

DOI: 10.1504/IJAIP.2024.138568

International Journal of Advanced Intelligence Paradigms, 2024 Vol.27 No.3/4, pp.249 - 265

Received: 25 May 2018
Accepted: 14 Jun 2018
Published online: 13 May 2024 *

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