Fake and Live Fingerprint Detection Using Local Diagonal Extrema Pattern and Local Phase Quantization

Abstract

Fingerprint is widely used physical human trait for uniquely identification and verification of human but use of fingerprint is becoming very challenging due to spoofing attacks. In this paper, we present new combination of local diagonal extrema pattern and local phase quantization descriptors to extract the features to generate feature vector for training and testing fingerprint images. Local diagonal extrema pattern finds the relationship between center pixels with diagonal neighboring pixels and local phase quantization extracts the local phase information by using short-term Fourier transform. LDEP reduces the dimensionality problem and forms a good combination of feature descriptor with LPQ. Combined extracted features of training and testing images using both descriptors are passed to Support Vector Machine for discriminating live and fake fingerprints. Experiments have been performed on LivDet2009 dataset and results show the effective and efficient performance of the proposed system. The proposed system achieved good accuracy and very less error rate in comparison to the different descriptors.