Low Cost Hand Vein Authentication System on Embedded Linux Platform

138 Abstract— Biometrics is one of the highly accurate technologies in the field of user identification. This paper presents a low costcontactless biometric identification system on Embedded Linux platform which is used to authenticate a person using the vein pattern in hand. As the system uses the vein pattern which is unique to each individual and is contained within human body, it is highly secure and accurate. Moreover, its contact less feature gives it a hygienic advantage over other personal authentication technologies. The system works by capturing a person’s vein pattern image by radiating it with near -infrared rays. The deoxygenated blood in the vein absorbs the near infrared radiation and thus the vein pattern appearsas black areas in the image. This captured pattern is stored as a template for the user verification. The experimental results of the proposed system shows that the dorsal hand vein pattern is highly unique and is a better alternative for other personal authentication systems. Also, the use of low cost ccd camera and open source Embedded Linux made the system cheaper than the conventional systems without risking accuracy.

[1]  Kenneth W. Tobin,et al.  Combining near-infrared illuminants to optimize venous imaging , 2007, SPIE Medical Imaging.

[2]  M. Subramani,et al.  Highly Secure and Reliable User Identification Based on Finger Vein Patterns , 2011 .

[3]  Tai-hoon Kim,et al.  Palm Vein Authentication System: A Review , 2010 .

[4]  Ahmed M. Badawi,et al.  Biometric Authentication Using Fast Correlation of Near Infrared Hand Vein Patterns , 2008 .

[5]  Shangling Song,et al.  An embedded real-time finger-vein recognition system for mobile devices , 2012, IEEE Transactions on Consumer Electronics.

[6]  Maleika Heenaye-Mamode Khan,et al.  A New Method to Extract Dorsal Hand Vein Pattern using Quadratic Inference Function , 2010, ArXiv.

[7]  Suchakrapani Datt Sharma,et al.  Low-cost subcutaneous vein detection system using ARM9 based single board computer , 2011, 2011 3rd International Conference on Electronics Computer Technology.

[8]  Dr.Ms.A.Ushapriya Mr.M.SUBRAMANI.  HIGHLY SECURE AND RELIABLE USER IDENTIFICATION BASED ON FINGER VEIN PATTERNS , 2011 .

[9]  M. Madheswaran,et al.  An Improved Multimodal Palm Vein Recognition System Using Shape and Texture Features , 2010 .

[10]  Christoph Busch,et al.  Vein Pattern Recognition Using Chain Codes Spatial Information and Skeleton Fusing , 2012, Sicherheit.

[11]  Ashwini,et al.  Biometric Authentication by Dorsal Hand Vein Pattern , 2012 .

[12]  Qin Li,et al.  Palm Vein Extraction and Matching for Personal Authentication , 2007, VISUAL.

[13]  Naoto Miura,et al.  Feature Extraction of Finger-vein Patterns Based on Repeated Line Tracking and Its Application to Personal Identification , 2022 .

[14]  Ajay Kumar,et al.  Personal Authentication Using Hand Vein Triangulation and Knuckle Shape , 2009, IEEE Transactions on Image Processing.

[15]  Hatim Aboalsamh.  A Multi Biometric System Using Combined Vein and Fingerprint Identification , 2010 .

[16]  Jeng-Shyang Pan,et al.  A Survey of Vein Recognition Techniques , 2010 .