Robust palmprint identification using efficient enhancement and two-stage matching technique

摘要

Palmprint-based human authentication has shown great potential for civil, forensic, and corporate security applications in recent years. Palmprint recognition systems suffer because of large palmprint sizes and the presence of a large number of creases and erroneous minutiae that make the enhancement and matching phases a challenge. In this study, a novel approach is presented based on efficient enhancement and a two-stage matching technique that demonstrates highly accurate identification results. The enhancement approach extracts minutia features from high-quality regions based on local ridge characteristics. The selected minutiae are then matched using a two-stage local and global minutiae neighbour-based matching technique. To demonstrate the performance of the proposed technique, comparisons with open-source algorithms are made based on equal error rate and detection error trade-off graph. The results confirm the efficacy of proposed palmprint enhancement and identification technique.