A Review of Biometric Identification in Signal Processing

This paper describes person identity by fingerprint, Face recognition, and voice information using Biometrics tool. The person is modeled by their features using Gaussian Mixture Model (GMM). Bio metrics is frequently used in signal processing applications. Thus, we concentrated on the methodology of biometrics for person identification which is useful in industrial and military security systems. The statistical values are measured by GMM in pattern recognition, Face recognition, and voice Recognition. These statistical values will helps for modeling of person using Bio-metric technique. The voice features are mapped into a Mel-Frequency-Cepstral-Coefficients (MFCC) form. The process of indentifying a person using MFCC data is described in this paper.