Abstract
The palm vein authentication technology is extremely safe, accurate and reliable as it uses the vascular patterns contained within the body to confirm personal identification. The pattern of veins in the palm is complex and unique to each individual. Its non-contact function gives it a healthful advantage over other biometric technologies. This paper presents an algebraic method for personal authentication and identification using internal contactless palm vein images. We use MATLAB image processing toolbox to enhance the palm vein images and employ coset decomposition concept to store and identify the encoded palm vein feature vectors. Experimental evidence shows the validation and influence of the proposed approach.
Highlights
Biometrics can be defined as an automated measurement of physiological or behavioral characteristics that are used to authenticate, determine or confirm identity of individuals [1]
How to cite this paper: Sayed, M. (2015) Palm Vein Authentication Based on the Coset Decomposition Method
At the present time many types of biometric systems are in use; the most widespread ones are fingerprints, face recognition, iris recognition, hand and finger geometry, voice print, signature identification, gait, DNA and dorsal hand vein
Summary
Biometrics can be defined as an automated measurement of physiological or behavioral characteristics that are used to authenticate, determine or confirm identity of individuals [1]. A user must be first enrolled in the system as a biometric template (or reference) This template is securely stored in a central database or on a smart card issued to the user. One of the upcoming highly secure, accurate and precisebiometric technologies is the personal identification using palm veins [7] It is the world’s first contactless authentication technology that uses the vein patterns in human palms to confirm a person’s identity [8]. For security reason, it is eligible that palm vein information is saved in a database (on a token or on a smart card) in encrypted arrangement, rather than in normal digital image. In this paper we apply an enhanced version of the coset decomposition algorithm [10] that uses syndrome bits as safe storage and decoding to palm vein templates. The algorithm should compute a bit string which will furnish access to the system even though the bit string is not shut to any of the stored palm vein templates
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