Image quality augmented intramodal palmprint authentication

This study serves dual objectives. First, as an efficient, in terms of speed and accuracy, wavelet-based intramodal palmprint authentication approach. Second, quantification of illumination, quality of palmprints and its incorporation in the score fusion for the classification performance enhancement. The later objective is realised using localised contrast measurement and quality-augmented fusion based on illumination sensitiveness of the features. The former objective is realised through intramodal feature extraction and fusion exploiting the multi-scale analysis of palmprint using wavelet transform. The intramodal features (energy, principal lines, dominant wrinkles and high-scale spatial patterns) are extracted in the wavelet domain thus significantly minimising the computational disadvantage of intramodal approach. Significant reduction in the equal error rate (EER) is observed upon match score fusion. Experimental results on PolyU-Online-Palmprint-Database (PolyU) of 386 classes show a relative improvement index of 71.75% with an overall EER of 0.14%; better than the state-of-the-art intramodal and wavelet-based approaches.