Paper Title
Multi-Instance Iris Template-Basedintruder Detection Using Minkowski Distance

Biometrics is the most widely used authentication procedure in the recent decade. A template matching-based iris authentication was carried out to expand the reliability and accuracy of identification with no time delay. A trustworthy and accurate biometric system is the iris recognition system. The crucial level in the iris-finding process is the localization of the iris boundaries in an eye picture. To segment the iris, several algorithms are available. Daugman's algorithm is one of the segmentation processes utilized in several commercial iris biometric devices. This work is to use the MATLAB programming environment to create this technique, and the developed technique was evaluated on a variety of eye pictures,including low contrast and photographs with a partially covered iris. [1, 10] The test results showed that Daugman's algorithmaccurately determines the margins of the iris in high-quality photographs. Further preprocessing of these photos has enhanced the algorithm's performance on the lower-quality images. We used the "Minkowski distance" for the suggested model in order to satisfy the non-linearity transformation criterion. When compared, this offers us findings with a 98.75% accuracy rate. Keywords - Biometrics, Template, Minkowski Distance Technique, Noninvertible Transformation, Daugman Algorithm.