MULTI-BIOMETRIC AUTHENTICATION SYSTEM USING FEATURE LEVEL FUSION

Advancements in science, technologies, industries and in numerous other fields have lead to the need for security improvements in order keep their valuables, workplace, societies, homes, etc., accessible only to authorized personnel. Biometric authentication is a well-known solution for this issue. One of the most unique patters can be obtained in finger veins which is also a unique physiological biometric. And since finger veins are beneath the skin, they are considered to be much reliable, secure and also know to be forge proof. Finger vein authentication system has proven to be a remarkable technology in the field of biometrics and are applicable where higher levels of security and privacy is very important. This paper, proposes a feature level fusion based system that uses finger vein features extracted from two algorithms namely DWT (Discreet Wavelet Transform) and canny edge detection. Results indicate better accuracy, higher TAR (True acceptance rate), lower TRR (True Reject Rate) and EER (Equal Error Rate) for feature level fusion in comparison with score level fusion technique.