Pattern matching for the iris biometric recognition system uses KNN and fuzzy logic classifier techniques
摘要
This research introduces novel iris biometric authentication methods employing wavelength rectangular coding (WRC) and enhanced isocentric segmentation (EISOS). By categorizing feature vectors from established datasets (CASIA, MMU, and UBIRIS) using KNN and fuzzy logic, our findings showcase heightened accuracy and decreased false acceptance and rejection rates compared to current methods, signifying advancements in secure person identification.