Palmprint Recognition using PCF and SURF

In Biometric Technology, Palm print recognition is one of the most reliable personal identification methods. In the present study an attempt was made to texture based palmprint identification using Phase-Correlation Function (PCF) and Speeded Up Robust Features (SURF). The PCF is an image matching technique using the phase components in 2D DFTs of given images. In SURF, a region of interest (ROI) is cropped for feature extraction and the key points are extracted with fast Hessian detector and an orientation invariant descriptor is constructed for each key point. Among the two methods, the SURF method can significantly achieved less EER without sacrificing recognition performance compared with Phase Correlation function. The implemented features and decision rules yields promising result of EER=6.488 % for verification rate.

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