International Research Journal of Engineering and Technology (IRJET)
e-ISSN: 2395 -0056
Volume: 04 Issue: 04 | Apr -2017
p-ISSN: 2395-0072
www.irjet.net
FINGER VEIN RECOGNITION Dr.S.Brindha1 1HoD,
Department of Computer Networking, PSG Polytechnic College, Coimbatore, Tamilnadu, India ---------------------------------------------------------------------***-------------------------------------------------------
Abstract - Vein based biometrics are gaining importance
due to their greater accuracy and security. Finger vein based biometric systems elegantly address problems present in fingerprint systems. The vein based authentication system is a promising biometric pattern for personal identification in terms of its security and convenience. The vein patterns can only be taken from a live body. Hence it is a natural and convincing proof that the subject whose veins are successfully captured is alive. Finger vein recognition technique is enhanced using neighborhood elimination technique to reduce the repeated feature set in the extracted finger vein minutiae image. Neighborhood elimination technique is employed for the purpose of removing the redundant information while keeping the effective source information for subsequent processing. Key Words: Biometrics, Finger vein, Image Processing, Authentication 1. INTRODUCTION User authentication is extremely important for computer and network system security. Some of the commonly used biometric traits[1] are face, sclera, fingerprint, iris, finger vein etc., The vein based authentication system is a promising biometric pattern for personal identification in terms of its security and convenience. It is difficult to steal since the vein is hidden inside the body and is mostly invisible to human eyes. The vein patterns can only be taken from a live body. Hence it is a natural and convincing proof that the subject whose veins are successfully captured is alive. Finger vein authentication is a new biometric method utilizing the vein patterns inside one’s fingers for personal identity verification[2]. Biometric systems based on fingerprints can be fooled with a dummy finger fitted with a copied fingerprint; voice and facial characteristicbased systems can be fooled by recordings and highresolution images. The finger vein ID system is much harder to fool because it can only authenticate the finger of a living person.
2. EXTRACTING FINGER VEIN FEATURES Finger vein patterns are captured by penetrating the finger with near infra-red rays to verify an individual’s identity. To obtain the pattern for the database record, an individual inserts a finger into an attester terminal containing a near-infrared LED light as shown in Figure 1 or a monochrome CCD camera. The haemoglobin in the blood absorbs near-infrared LED light, which makes the vein system appear as a dark pattern of lines.[4] The © 2017, IRJET
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Impact Factor value: 5.181
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camera records the image and the raw data is digitized, certified and sent to a database of registered images.
Figure 1 Finger vein sensor Gabor filters are used as band pass filters to remove the noise and preserve true ridge/valley structures. In the finger images, there are many unwanted regions that are to be removed by choosing the interested area in that image. The useful area is said to be “Region of Interest”[3]. The obtained binary mask is used to segment the ROI from the original finger-vein image. ROI extraction is done by the two morphological operations called “OPEN” and “CLOSE”. The “OPEN” operation can expand images and remove peaks introduced by background noise. The “CLOSE” operation can shrink images and eliminate small cavities. The bound is the subtraction of the closed area from the opened area. Then the algorithm removes the leftmost, rightmost, uppermost and bottommost blocks out of the bound so as to get the tightly bounded region just containing the bound and inner area. The centerlines are detected by searching for positions where the curvatures of a cross-sectional profile of a vein image are locally maximal. In this method, the centerlines of the veins can be extracted consistently without being affected by the variations in the width and brightness of the vein. The vein pattern is detected as shown in Figure 2.
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Figure 2 .(a) Input image (b) Binarized image (c) Filtered image using Gabor filter (d) ROI image (e) Extracted veins (f) Minutiae points ISO 9001:2008 Certified Journal
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