A Hybrid Model of Multimodal Approach for Multiple Biometrics Recognition

Abstract

A single biometric identifier in making a personal identification is often not able to meet the desired performance requirements. Biometric identification based on multiple biometrics represents an emerging trend. Automated biometric systems for human identification measure a “signature†of the human body, compare the resulting characteristic to a database, and render an application dependent decision. These biometric systems for personal authentication and identification are based upon physiological or behavioral features which are typically distinctive, although time varying, such as Face recognition, Iris recognition, Fingerprint verification, Palm print verification in making a personal identification. Multi-biometric systems, which consolidate information from multiple biometric sources, are gaining popularity because they are able to overcome limitations such as non-universality, noisy sensor data, large intra-user variations and susceptibility to spoof attacks that are commonly encountered in uni-biometric systems. In this paper, it addresses the concept issues and the applications strategies of multi-biometric systems.