A novel Approach to improve biometric authentication using Steerable-Locality Sensitive Discriminant Analysis
Journal of Al-Qadisiyah for Computer Science and Mathematics,
2017, Volume 9, Issue 1, Pages 61-70
AbstractWith the increasing needs in security systems, palm vein authentication is one of the important and reliable solutions for identity security for biometrics based authentication systems. Palm vein, as a biological characteristic of an individual, has been increasingly utilized for personal authentication in advanced security applications. Palm vein patterns are a unique attribute of everyone and can therefore be used as a biometric characteristic. The human palm vein pattern is extremely complex and it shows a huge number of vessels. The biometric information is located inside the human body, and therefore it is protected against forgery and manipulation. In the proposed method, the Multilevel Gaussian-Second-Derivative (MGSD) is proposed for enhancement the palm vein images. Secondly, a new feature extraction method based on Steerable filter and Locality Sensitive Discriminant Analysis is proposed called Steerable - Locality Sensitive Discriminant Analysis (SLSDA). Finally, the Correlation Distance method is proposed for verify the tested palm vein. The EER to the proposed authentication system is 0.1087%.
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