Multimodal biometric identification system based on face and fingerprint

A biometric system which is based only on a single biometric identifier in making a personal identification is often not able to meet the desired performance requirements. Multimodal biometrics is an emerging field of biometric technology, where more than one biometric trait to improve the combined performance. We introduce a bimodal biometric system which integrates face and fingerprint. This system takes advantage of the capabilities of each individual biometrics. It can be used to overcome some of the limitations of a single biometrics, increases the performance and robustness of identity authentication systems. In this context, a key matter is the fusion of a two different modality to obtain a final decision of classification. We propose to evaluate a binary classification schemes: support vector Machine to carry on the fusion. The experimental results show that merging multiple biometrics can help to reduce the error rate of the system. Keywords— Binary classifiers, biometrics, data fusion, face recognition, fingerprint recognition, support vector machine.