Developing a multimodal biometric authentication system using soft computing methods

Robust personal authentication is becoming ever more important in computer-based applications. Among the several methods, biometric offers several advantages, mainly in embedded system applications. Hard and soft multi biometric, combined with hard and soft computing methods can be applied to improve the personal authentication process and to generalize the applicability. This chapter describes the embedded implementation of a multi biometric (voiceprint and fingerprint) multimodal identification system based on hard computing methods (DSP) for features extraction and matching, an artificial neural network (ANN) for soft feature pattern matching, and a fuzzy logic engine (FLE) for data fusion and decision.