Abstract
Palm-Vein Biometric Authentication system is a physiological pattern recognition technique that uses the vein patterns of an individual's palm for providing authentication. This paper presents a comprehensive comparative study of basic transforms: PCA (Principal Component Analysis), DCT, DST, Walsh-Hadamard and Slant for Palm Vein recognition. These transforms were implemented on a database consisting of 576 images, containing unmodified as well as modified images after noise introduction, brightness and contrast changes in the original images. Performance evaluation metrics FAR (False Acceptance rate), FRR (False Rejection Rate) and EER (Equal Error Rate) have been obtained. Then, comparative analysis of these methods has been done on the basis of performance evaluation metrics obtained, robustness of implemented system, feature vector size and time taken for execution. Results obtained showed that Walsh-Hadamard transform performs the best and can be successfully used for Palm Vein biometrics.
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