scispace - formally typeset
Open AccessJournal Article

Retinal Image Analysis for Biometrics

Reads0
Chats0
TLDR
A design of retinal image analysis using feature detection and feature matching techniques is proposed and it is shown that the main limitation of this process lies in the image acquisition.
Abstract
A design of retinal image analysis using feature detection and feature matching techniques is proposed. Biometric systems perform person's authentication based on one’s physical features. A number of biometric systems has been developed in the last few years such as fingerprints, iris etc. The retinal scans serves the biometric based security systems since the unique pattern of blood vessels serves the purpose. The retinal images are acquired from the DRIVE and STARE database and various feature detection algorithms are used to detect and extract features. The original image is recovered from the distorted image using MSAC algorithm and the extracted features are then compared and feature matching is done to identify the amount of matching to identify and authorize the person. The main limitation of this process lies in the image acquisition. Hence retinal image database is used as the source of

read more

Content maybe subject to copyright    Report

References
More filters
Journal ArticleDOI

Locating blood vessels in retinal images by piecewise threshold probing of a matched filter response

TL;DR: An automated method to locate and outline blood vessels in images of the ocular fundus that uses local and global vessel features cooperatively to segment the vessel network is described.
Journal ArticleDOI

Detection of blood vessels in retinal images using two-dimensional matched filters

TL;DR: The concept of matched filter detection of signals is used to detect piecewise linear segments of blood vessels in these images and the results are compared to those obtained with other methods.
Book ChapterDOI

The Modularity of Mind: An Essay on Faculty Psychology

TL;DR: This monograph synthesizes current information from the various fields of cognitive science in support of a new theory of mind that postulates a vertical and modular psychological organization underlying biologically coherent behaviours.
Journal ArticleDOI

An Ensemble Classification-Based Approach Applied to Retinal Blood Vessel Segmentation

TL;DR: This method uses an ensemble system of bagged and boosted decision trees and utilizes a feature vector based on the orientation analysis of gradient vector field, morphological transformation, line strength measures, and Gabor filter responses to segmentation of blood vessels in retinal photographs.
Journal ArticleDOI

Deep convolution neural network for accurate diagnosis of glaucoma using digital fundus images

TL;DR: An eighteen layer CNN framework is proposed for glaucoma diagnosis with the highest accuracy of 98.13% using 1426 fundus images, which demonstrates the robustness of the system, which can be used as a supplementary tool for the clinicians to validate their decisions.