A Comparative Study on Fusion Strategies in Multimodal Biometric System

Most of the business applications use biometrics to authenticate and verify the person when a transaction is made. Biometric systems are of two types: unimodal and multimodal. unimodal biometrics use only single trait like fingerprint, iris, face and retina (physiological trait) or gait, voice, handwritten (behavioral trait) to verify the person. But it suffers from some limitations of noise in sensed data, intra-class variation, inter-class similarities, non-universality and spoof attacks. Multimodal biometric systems overcome some of these limitations through fusion process. Multimodal biometric system provides more accuracy when compared to unimodal biometric system. The main goal of multimodal biometric system is to develop the security system for the areas that require high level of security. a reliable and successful multimodal biometric system needs an effective fusion scheme to combine biometric characteristics derived from one or modalities. The goal of fusion is to determine the best set of experts in a given problem domain and helps to minimize the error rate. It also improves accuracy, efficiency, and system robustness and fault tolerance. In this survey different fusion techniques of multimodal biometrics have been discussed.