Science and Development Network (SciDev.Net)
This paper describes a combined behavioral techniques based on speech and signature biometrics modalities. Fusion of multiple biometric modalities for human verification performance improvement has received considerable attention. 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 mono modal biometric systems. Soft decision level fusion based Gaussian Mixture Models (GMM), in which the (EM) and (GEM) algorithms for estimating the parameters of the mixture model and the number of mixture components have been compared.