Description

Abstract:

Multimodal biometric identification technique utilizes two or more individual modalities to improve the identification accuracy and overcome some problems existing in conventional unimodal methods.  This paper presents a multimodal biometric identification approach based on the features of Ear and Iris. We use physical features to check a person’s identity which ensure much greater security than password and number systems. These systems are based on human traits which, unlike passwords or pins, cannot be lost, stolen or forgotten. One such trait is ear. With the initial doubts on uniqueness of ear, ear biometrics could not attract much attention. But after it has been said that it is almost impossible to find two ears with all the parts identical, ear biometrics has gained its pace. Here geometrical features are used to extract ear features and wavelet features are extracted from iris localized images. Finally these features are fused and subjected to hamming distance measure to check for identification.