# Individuals Identification Based on Palm Vein Matching under a Parallel Environment
## 5 Results  
In this section, the performance of the proposed method for palm vein recognition is evaluated. Three different datasets have been tested in our experiments: CASIA Multi-Spectral Palmprint Image Database V1.0 (CASIA-MS-PalmprintV1 for short) [46], collected by the Chinese Academy of Sciences' Institute of Automation (CASIA); VERA Palm vein database [66], by Idiap Research Institute; and PUT Vein database [67], created by Institute of Control and Information Engineering (CIE). All three are publicly available and they can be found in the evaluations of most of the works presented in the literature. The first two databases are based on contactless acquisition, while the other one used a contact acquisition device. The CASIA Multi-Spectral Palmprint Image Database [46] is the most relevant dataset for palm print and palm vein recognition. It contains 7200 palm images captured from 100 different people using a self-designed multiple spectral imaging device. All palm images are eight bit gray-level JPEG files with a resolution of \(768\times 576\) pixels. For each hand, two sessions of palm images were captured with a time interval of more than one month. In each session, there are three samples that contain six palm images that were captured using six different wavelengths (visible, 460, 630, 700, 850 and 940 nm) of the illumination. Between two samples, the authors allowed a certain degree of variations of hand postures aiming to increase the diversity of intra-class samples and simulate practical use. In this paper, we only use a portion of the database. To evaluate the proposed method, we use 1200 palm vein images of both hands, which were captured at a wavelength of 850 nm. Figure 6: Task distribution scheme where each row represents a similarity test. VERA Palm vein database [66] consists of 2200 images depicting human palm vein patterns. Palm vein images were acquired at a wavelength of 940 nm from 110 volunteers (70 male and 40 female) for both left and right hands. For each subject, images were obtained in two sessions of five pictures each per hand. All palm images are 8 bit gray-level using PNG format with a resolution of 480 \(\times\) 680. The database was acquired by a contactless device. However, the distance between the user hand and the camera lens is measured by an ultrasound sensor and an LED signal that indicates the user the correct position of the hand for the acquisition, which seems to be more natural and feasible. PUT Vein database [67] consists of 2400 images from 50 volunteers, half of palm vein pattern (1200 images) and the other half contains a wrist vein pattern (another 1200 images), for both left and right hands. Images were acquired by a contact acquisition system where the user covers the acquisition window with his or her palm or wrist, cutting off external light sources. Thus, all images have stable lighting conditions at a wavelength of 880 nm. For each subject, images were obtained in three series of four pictures each. Series were separated by intervals of at least one week on the same day of the week at the same time of day. Each obtained image is a 1280 \(\times\) 960 bitmap saved in BMP format. Typically, and depending on the application context, a biometric system operates in two different modes [2]: verification and identification. The verification mode is a positive recognition process, where the user claims a particular identity to the system by submitting its biometric trait sample. In response, the biometric system validates the claimed identity by making a 1:1 (one-to-one) comparison between the submitted sample and the enrolled template associated with this particular individual. The applications include user authentication on computers, ATMs, e-commerce, mobile devices, among others. On the other hand, in the identification mode, the biometric system tries to recognize an individual by making 1:N (one-to-many) comparisons with the submitted biometric sample to all the enrolled templates in the database, without knowing a specific identity for the user.