Advanced Touchless Biometric Identification using SIFT Features

The motto of this paper is to provide an efficient Biometric Identification using Multimodal Touchless Finger Print Acquisition and Mosaicking Technique. Fingerprints are traditionally captured based on contact of the finger on paper or a platen surface. This often results in partial or degraded images due to improper finger placement, skin deformation, slippage and smearing, or sensor noise from wear and tear of surface coatings. A new generation of touchless live scan devices that generate 3D representation of fingerprints is appearing in the market. This new sensing technology addresses many of the problems stated above. Single-view acquisition systems bring in problems, such as scene difference and a limited effective area. This paper thus presents a touchless multiview fingerprint capture system that acquires three different views of fingerprint images at the same time. This device is designed by optimizing parameters regarding the captured fingerprint image quality and device size. A fingerprint mosaicking method is proposed to splice together the captured images of a finger to form a new image with a larger useful print area. In this paper,tScale Invariant Feature Transformation(SIFT) algorithm and Random Sample Consensus techniques are used for better biometric identification. Keywords— SIFT, 3D, OTP, Finger Print Recognition, Bio Metrics,Multimodal Bio Metric Systems