Abstract
A person's fingerprint, palm print, palm vein, finger vein, retina, and iris are among the many biometric identities that are linked to them. For applications like authorisation systems, attendance systems, and others, people are recognised by their biological identities. Nearly every company with a medium-sized to big workforce has adopted biometric technology. A large number of small businesses with a sizable workforce are also implementing biometric solutions. Iris-based biometric systems are becoming more and more popular as stand-alone, hybrid, or combined biometrics with other authenticating entities. Accurate localisation of the iris characteristics from the ocular image gathered for training or testing is necessary for iris identification. Two demarcation circles are needed for iris extraction; the first circle marks the outer boundary, and the second circle marks the inner boundary by identifying the pupil's outer boundary. For precise localisation of the region of interest containing the iris feature, the angular shift mechanism can also be used to examine the movement of the iris in the provided image. The suggested method would identify the iris features with or without contact lenses using probabilistic classification based on the multi-class SVM. The suggested remedy is to enhance the current model for reliable performance.
Keywords
IRIS Recognition, Probabilistic Classification, Moved Feature Localization, Authorization Systems, Etc.
Citations
IRE Journals:
K. Mani Raju, Gattu Ramya, Nagavelli Yogender Nath, R. Prasanth Reddy "A Review On Biometric Authentication Using Adaptive Iris Features" Iconic Research And Engineering Journals Volume 7 Issue 10 2024 Page 622-628 https://doi.org/10.64388/IREV7I10-1712450
IEEE:
K. Mani Raju, Gattu Ramya, Nagavelli Yogender Nath, R. Prasanth Reddy
"A Review On Biometric Authentication Using Adaptive Iris Features" Iconic Research And Engineering Journals, 7(10) https://doi.org/10.64388/IREV7I10-1712450
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