IRIS AND FINGER VEIN MULTI MODEL RECOGNITION SYSTEM BASED ON SIFT FEATURES

Individual identification process is a very significant process that resides a large portion of
day by day usages. Identification process is appropriate in work place, private zones, banks …etc.
Individuals are rich subject having many characteristics that can be used for recognition purpose such
as finger vein, iris, face …etc. Finger vein and iris key-points are considered as one of the most talented
biometric authentication techniques for its security and convenience. SIFT is new and talented
technique for pattern recognition. However, some shortages exist in many related techniques, such as
difficulty of feature loss, feature key extraction, and noise point introduction. In this manuscript a new
method named SIFT-based iris and SIFT-based finger vein identification with normalization and
enhancement is proposed for achieving better performance. In evaluation with other SIFT-based iris or
SIFT-based finger vein recognition algorithms, the suggested technique can overcome the difficulties of
accurate extraction of key-points and clear the noise points without feature loss. Experimental
outcomes demonstrate that the normalization and improvement steps are critical for SIFT-based iris
recognition and SIFT-based finger vein recognition , the recommended method can accomplish
satisfactory recognition performance.