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Dynamic Audio-Visual Client Recognition modelling
Tijjani Adam Shuwa, U. Hashim
Pages - 512 - 526     |    Revised - 01-11-2011     |    Published - 15-12-2011
Volume - 5   Issue - 5    |    Publication Date - November / December 2011  Table of Contents
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KEYWORDS
Facial Recognition, Audio- Visual Client Recognition, Discriminate, Multi-model Biometric System, Training Image, PCA, LDA.
ABSTRACT
This paper contains a report on an Audio-Visual Client Recognition System using Matlab software which identifies five clients and can be improved to identify as many clients as possible depending on the number of clients it is trained to identify which was successfully implemented. The implementation was accomplished first by visual recognition system implemented using The Principal Component Analysis, Linear Discriminant Analysis and Nearest Neighbour Classifier. A successful implementation of second part was achieved by audio recognition using Mel-Frequency Cepstrum Coefficient, Linear Discriminant Analysis and Nearest Neighbour Classifier the system was tested using images and sounds that have not been trained to the system to see whether it can detect an intruder which lead us to a very successful result with précised response to intruder.
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Dr. Tijjani Adam Shuwa
Institute of Nano Electronic Engineering Universiti Malaysia Perlis Kangar, 01000, Malaysia - Malaysia
tijjaniadam@yahoo.com
Professor U. Hashim
Unimap - Malaysia