Personal Identification based on Multi Biometric Traits

The biometric system that based on single biometric measure (Unimodal) are usually contained variety of problems and limitation like noisy data, does not provide high security and non-university, so we used the multibiometric system to improve the recognition rate, get better security than the unimodal systems and higher efficiency. This study aims to identify a person by using multibiometric traits (Signature, Face and Fingerprint) by using different technique (Singular Value Decomposition (SVD,PCA and wavelet energy). The quality and accuracy of the identification and recognition of the person are measured in this system by computing the Peak Signal to Noise Ratio (PSNR) and the Mean Square Error (MSE) for face, fingerprint, and signature.