Palmprint Recognition System Based on Multi-Block Local Line Directional Pattern and Feature Selection

In this paper, the authors deal with multimodal biometric systems based on palmprint recognition. In this regard, several palmprint-based approaches have already been proposed. Although these approaches show interesting results, they have some limitations in terms of recognition rate, running time, and storage space. To fill this gap, the authors propose a novel multimodal biometric system combining left and right palmprints. For building this multimodal system, two compact local descriptors for feature extraction are proposed, fusion of left and right palmprints is performed at feature -level, and feature selection using evolutionary algorithms is introduced. To validate the proposal, the authors conduct intensive experiments related to performance and running time aspects. The obtained results show that the proposal shows significant improvements in terms of recognition rate, running time, and storage space. Also, the comparison with other works shows that the proposed system outperforms some literature approaches and is comparable with others.