An Efficient Algorithm for Multimodal Biometric Face Recognition using Speech Signal

Multimodal biometric systems for today’s high security applications must meet stringent performance requirements. The fusion ofmultiple biometrics helps to minimize the system error rates. Fusion methods include processing biometric modalities sequentially until anacceptable match is obtained. More sophisticated methods will combine scores from separate classifiers for each modality. Multi algorithmapproach employs a single biometric sample acquired from single sensor. Two or more different algorithms process this acquired sample. Theindividual results are combined to obtain an overall recognition result. This approach is attractive, both from an application and research point ofview. In recent years much advancement have been made in face recognition techniques to cater to the challenges such as pose, expression, illumination, aging and disguise. However, due to advances in technology, there are new emerging challenges for which the performance of facerecognition systems degrades and plastic/cosmetic surgery is one of them. In this paper we comment on the effect of plastic surgery face imagein multimodal biometric face recognition using text dependent speech signal