palm vein technology and its applications

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Akhil Kumar

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Introduction The term “biometrics” is derived from the Greek words “bio” (life) and “metrics” (to measure). Automated biometric systems have only become available over the last few decades, due to significant advances in the field of computer processing. Many of these new automated techniques, however, are based on ideas that were originally conceived hundreds, even thousands of years ago. One of the oldest and most basic examples of a characteristic that is used for recognition by humans is the face. Since the beginning of civilization, humans have used faces to identify known (familiar) and unknown (unfamiliar) individuals. This simple task became increasingly more challenging as populations increased and as more convenient methods of travel introduced many new individuals into- once small communities. The concept of human-to-human recognition is also seen in behavioral-predominant biometrics such as speaker and gait recognition. Individuals use these characteristics, somewhat unconsciously, to recognize known individuals on a day-to-day basis.

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This paper presents an optimized palm vein authentication algorithm which will match the similar type of vascular pattern from the database given i.e. CASIA-Palmprint V1 dataset. . The palm vein authentication technology offers a high level of accuracy. Palm vein authentication uses the vascular patterns of an individualÃ¢â‚¬â„¢s palm as personal identification data. If we compare with a finger or the back of a hand, a palm has a broader and more complicated vascular pattern and thus contains a wealth of differentiating features for personal identification. The importance of biometrics in the current field of Security has been depicted in this work. Also, we have also outlined opinions about the utility of Biometric authentication systems. We have processed the raw image from the dataset before implementing authentication algorithm. After getting the suitable image after pre- processing, we have used local binary pattern (LBP) for feature extraction purpose & then using a machine learning algorithm, with support vector machine (SVM), we tried to match the vascular vein pattern for authentication. Result of the matching algorithm is not only optimized as per the proposed approach but also quite efficient.

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Abstract— A biometric feature provides a high security access system. Traditional method uses PIN number, password, key, and etc to identify a person is unreliable and provide a low level security. It provides more reliable feature than the password based authentication system as biometric characteristic cannot be lost or forgotten, biometric feature are difficult to replicate, and require the person to be present for the authentication process. Many biometric such as face , finger print, iris and voice have been developed. But here verification using vein pattern is less developed. Biometric authentication is perform in insecure because of information leakage issue, so overcome this the implementation of biometric hand vein authentication Hand vein patterns are the vast network of blood vessels underneath a person’s skin. Index Terms— Biometric, Hand vein structure, Authentication

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