# Individuals Identification Based on Palm Vein Matching under a Parallel Environment
## 1 Introduction
In this sense, the execution time of the recognition process has a great influence and it is fundamental  
Figure 1: Effects of deformations on different samples of palm vein images from the CASIA Multi-Spectral Palmprint Image Database V1.0 [46]. for a real-world implementation. Thus, the proposal of this paper reduces the execution time of the dense correspondences between palm vein images, by both using an efficient sparse matching algorithm that achieves state-of-the-art accuracy but running much faster than the dense matching method, and implementing a multi-core parallel scheme for accessing and querying the database. The proposed method aims to provide an effective and efficient technique to obtain similarity of palm vein images considering their displacements as discriminatory information. Our proposal aims to prove that deformation information of palm vein images is an effective method for palm vein recognition. Thus, we propose using a sparse matching algorithm as an alternative for estimating the displacement, in contrast to [45] that uses a dense matching process. Hence, the goal of this work is to propose a new method for contactless palm vein systems, which should be able to overcome problems of real-world systems and suitable for real-time individuals identification. Consequently, our approach has three main contributions:  
* First, we introduce a new perspective to deal with deformations on contactless palm vein systems, which is based on the ideas presented in [45]. Our method uses deformations as discriminative information for palm vein recognition. Thus, we reduce the influence of deformations for real-world systems by ensuring the robustness of palm vein recognition. To the best of our knowledge, the method we present is the first that aims to reduce the influence of deformations by using it as discriminative information for palm vein recognition. * Second, in order to reduce the number of comparisons during the matching process, we propose using a sparse matching algorithm [52], which employs a novel coarse-to-fine matching scheme based on a combination of random search and propagation between hierarchical levels. This method is robust to image displacements and more efficient than dense correspondences using SIFT proposed by [45], in terms of execution time achieving a speed-up above 15\(\times\). The details of the proposed descriptor and matching algorithm are presented in Sections 3.2 and 3.3. * Third, with the aim of increasing the number of queries per second, considering a real-world implementation, a master-worker scheme is proposed under a multi-core platform. The master process is responsible for controlling queries and collecting the results, and, on the other hand, the worker processes are used to obtain the similarity score between images. See Section 4 for more details. The rest of the paper is organized as follows. First, Section 2 reviews the fundamental concepts and techniques related to palm vein recognition and image matching methods based on optical flow. Section 3 introduces the theoretical aspects that support the proposed method based on displacement information. In Section 4, the proposed multi-core scheme for people massive identification using palm vein patterns is presented. Finally, the experimental results are discussed in Section 5, and the conclusions are given in Section 6.