Computer Science – Computer Vision and Pattern Recognition
Scientific paper
2012-04-19
International Journal of Computer Applications 35(7):17-21, December 2011
Computer Science
Computer Vision and Pattern Recognition
5 pages, 11 figures. arXiv admin note: text overlap with arXiv:1201.3720 and arXiv:1204.1177
Scientific paper
With the advancement of communication and security technologies, it has become crucial to have robustness of embedded biometric systems. This paper presents the realization of such technologies which demands reliable and error-free biometric identity verification systems. High dimensional patterns are not permitted due to eigen-decomposition in high dimensional feature space and degeneration of scattering matrices in small size sample. Generalization, dimensionality reduction and maximizing the margins are controlled by minimizing weight vectors. Results show good pattern by multimodal biometric system proposed in this paper. This paper is aimed at investigating a biometric identity system using Support Vector Machines(SVMs) and Lindear Discriminant Analysis(LDA) with MFCCs and implementing such system in real-time using SignalWAVE.
Ali Asar
Farhan Muhammad
Khan Aamir
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