An Efficient Authentication Using Fusion of Different Modalities

Abstract

Biometrics is the science and technology of measuring and analyzing biological data of human body, extracting a feature set from the acquired data, and comparing this set against to the template set in the database. Biometric systems have now been deployed in various commercial, civilian and forensic applications as a means of establishing identity. The biometric system is one such that can provide accurate and reliable scheme for person verification. Biometric systems are of two types: unimodal and multimodal.:Unimodal Biometric systems based solely on one-modal biometrics are often not able to meet the desired performance requirements for large user population applications, due to problems such as noisy data, intra-class variations, restricted degrees of freedom, non-university, spoof attacks, and unacceptable error rates. Multimodal biometrics refers to the use of a combination of two or more biometric modalities in a single identification system. The multimodal biometrics are; face and finger print, face and iris/, iris and finger print etc. In this paper we have concentrated in fusion of face and iris for multimodal biometric authentication. We adopted a new approach called the contourlet transform is a new extension of the wavelet transform in two dimensions using multi-scale and directional filter banks for iris feature extraction.