Application of 1-D Wavelet Transform in Speaker and Face Verification

• Main Authors: Jia Der CHU, 朱家德
• Other Authors: Ching-Han CHEN
• Format: Others
• Language: zh-TW
• Published: 2003
• Online Access: http://ndltd.ncl.edu.tw/handle/59740085959243294870

碩士 === 義守大學 === 電機工程學系 === 91 === This paper will study two problem in biometrics ─ speaker and face recognition. Firstly, to speaker recognition problem, we use wavelet transform to decompose speech signal into high and low frequency coefficients, then we apply difference traditional methods include PCA, LPCC, Fractal, and WTFT to extract low or high frequency as feature, which combined probabilistic neural network classifier to match voiceprint. This shows the proposed method will improve recognition rate and efficiency. Besides, to face recognition, we will obtain cumulative gray curve after 2D face image projected in horizon. Using discrete wavelet transform extracts low frequency coefficients as feature. For face identification and face matching application modes, we precede a set of experiments. The facial images are sampled from ORL database.Our experiments reveal that the proposed method possesses excellent recognition performance and efficiency. It is advantageous to realize a facial recognition system in a hardware-friendly, resource-constrained embedded environment.