Abstract: Biometric systems are available at present are more often used for identification and verification in various security applications. Face, Fingerprint, Iris are the biometric traits, frequently used in the present authentication system, its features offer simplicity of use and reliability. Biometric features are unique in nature, so this type of method can be used to avoid typical problem of systems based on use of password which can be forgotten or stolen.To keep a good level of security, spoofing detection tools are preferably implemented as software modules. The research in this field is very active with extracting the features of local descriptor based on the analysis of micro-textural features like Local Binary Pattern (LBP).The term biometric is becoming highly important in security world. The recent year researches are aim to increase the accuracy and quality of the livenesss detection. Finger print system can be possible to fool by reproducing the biometric pattern on simple moulds made of materials such as silicone, clay or gelatine. Iris-based systems can be fooled with sophisticated 3D masks.To enhance the accuracy and quality of biometric systems, many works has been conducted in the liv-ness detection. LBP, CoA-LBP, LPQ, WLD local descriptor and distortion method are used for the recognition works and these extracted components and templates are the processed to build the discriminative features used to linear kernel SVM classifier.
Keywords: Specular reflection, Image blurriness, Image Chromaticity, Color diversity, Image Distortion Analysis.