title: Developing a multimodal biometric authentication system using soft computing methods.
abstract: Robust personal authentication is becoming ever more important in computer-based applications. Among a variety of 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 feature extraction and matching, an artificial neural network (ANN) for soft feature pattern matching, and a fuzzy logic engine (FLE) for data fusion and decision.
authors.affiliation: Department of Computer Science, Universita degli Studi di Milano, Via Comelico 39, 20135, Milan, Italy, malcangi@di.unimi.it.
authors.forename: Mario
authors.initials: M
authors.lastname: Malcangi
mesh_terms: D000465:Algorithms; D056667:Biometric Identification / Q000379:methods*; D003201:Computers; D003878:Dermatoglyphics; D017143:Fuzzy Logic; D016571:Neural Networks, Computer; D049250:Speech Recognition Software