Analysis of Palmprint and Palmvein Authentication Using Scale Invariant Feature Transform(SIFT) Features

Abstract

Securing the information has been a major issue now a days and depending on the requirements and security reasons most of the authentication systems are moved from passcodes, pass cards to biometric systems where the metrics are derived from human features. Some of the major biometrics vastly used are Iris, fingerprint, voice recognition, face recognition. But there exists some other biometrics which can be used to increase the security level like palmvein pattern. For this project palmprint and palmvein patterns are selected because both the metrics need to be extracted from same region of palm. By applying Scale Invariant Feature Transform (SIFT) method on the biometrics palmprint and palmvein patterns we can analyze which metric is better and the efficiency in authentication by using different matching techniques. The aim of the project was to analyze the performance of SIFT on palmvein patterns and the palmprint to know which is more secure because even though both the metrics are extracted from the same region it is difficult to forge the palmvein pattern when compared to palm print.