Iris Recognition Through Feature Extraction Methods: A Biometric Approach

Abstract

Security has been one of the most passionately debated topics of science for decades, but its importance is growing exponentially as the amount of data collected by users grows. Verification and authentication have gotten a lot of attention in the security paradigm. With the passage of time, identifying a user's identity is becoming increasingly difficult. Many attempts have been done in this area, particularly with the use of human gestures such as fingerprints, face detection, palm print, retina detection, DNA test, heartbeat, speech checker, and so on. The most essential stage in this work is feature extraction, which extracts the iris' distinctive characteristics. In order to extract the distinguishing characteristic that is unique to each individual, several approaches have been presented. The goal of this study is to suggest the Gabor filter and Wavelet along with low and high-pass filters to deconstruct iris data and extract a unique pattern for iris recognition. The study investigates it. Because wavelet is the most sable means of image processing, the study investigates it.