Biometric Template Generation Framework Using Retinal Vascular Structure

Biometric identification devices depend on some characteristics of human body such as face, fingerprint, hand palm, eye etc. Among all these features, vascular structure based retinal biometry provides the most secure person identification system. In this paper, we propose biometric authentication framework with some existing and unique features present on human retinal vascular structure. The approach begins with segmentation from colored fundus images, followed by selecting unique features like center of optic disc (OD), macula, the distance between OD and macula, bifurcation points and their angles. A 96 bytes digital template is prepared then against each image by concatenating every selected features and finally, every template is compared with each other for finding dissimilarity. The study shows around 92% accuracy in template preparation and matching on all the images of DRIVE database.

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