Bimodal person identification system based on speech and signature recognition's - Gunawan, Teddy Surya (s.n, 2013)

(untitled)
This research work aims to develop automatic person identification systems based on three approaches including speech, hand signature, and bimodal biometric technologies. In order to develop the speech system, the Mel-Frequency Cepstral Coefficient (MFCC) and the Vector Quantization (VQ) are used, whereas the hand signature system is based on global features and Multilayer Perceptron (MLP) architecture for Artificial Neural Network (ANN). The bimodal system is based on fusing the speech and hand signature systems at decision level