Biometric Solution for Person Identification Using Iris Recognition System

The features extracted from the human iris can identify individuals even among genetically identical twins. A human iris is fully formed six months after birth and is invariant to physical changes, such as illness or pregnancy, as is the retina (e.g., diabetic retinopathy). As a central component of the Iris recognition system, we present an iris analysis technique that aims to extract and compress the unique features of a given iris with a discrimination criterion using limited storage. The compressed features should be at maximal distance with respect to a reference iris image database. The iris analysis algorithm performs several steps such as the algorithm detects the human iris by using a new model which is able to compensate for the noise introduced by the surrounding eyelashes and eyelids, it converts the isolated iris using a wavelet transform into a standard domain where the common radial patterns of the human iris are concisely represented, and It optimally selects, aligns, and near-optimally compresses the most distinctive transform coefficients for each individual user. Index Terms —Iris Analysis, Support vector machine(SVM), Wavelet coefficients, Feature extraction, Principal Component Analysis (PCA), Discrete Wavelet transform (DWT).