Fingerprint detection technique using SURF, PHOG & PCA feature extraction process

Abstract

The biometric way of identifying a person are wildly spared around many industries and organizations. The identification techniques followed for the biometric are mostly common in using fingerprint detection for individual identification. Basically password based security systems are cracked through many techniques, which makes many problem to the organization using password for security purpose. The spoof fingerprint way of identifying a person is becoming very famous in providing security to the users. The research work focuses on proposing a novel approach in merging fingerprint features all together in one static software approach. The features identified from the fingerprints are extracted using histogram equations in initial step of fingerprint security system. The Gabor wavelet transformation techniques is one of the images processing technique used for identifying features. The features are maintained carefully with applying dynamic score level integration. The efficiency of proposed work is checked with LivDet 2011 dataset. The rate of classification shows 9.625% and error rate is 2.27%.