The Dorsal Hand Dataset For Recognition System

Researchers are becoming increasingly interested in dorsal hand vein biometrics because of their characteristics. These characteristics can be summarized as follows: it does not need contact with the capture device, cannot be forged, does not change over time, and provides high accuracy. Recognition systems of the dorsal hand rely on how the collected images captured from the device are good. Near-infrared (NIR) light is used to distinguish veins from the back of the hand.Contactless hardware was used to capture images of the proposed system. The hardware consists of three components: a USB camera, infrared LEDs, and a mobile smartphone. The USB-Camera has a resolution of 640×480 pixels and was modified to be sensitive to infrared light by removing the infrared cut-off filter and placing another one made of a magnetic film that only wavelengths above 700 nm can pass. For illumination, 20 infrared LEDs were mounted on a test board and connected to a power supply. The dorsal hand is illuminated with infrared LEDs, and the camera starts capturing frames and sends them to the smartphone mobile via the On-The-Go cable (OTG) for further processing.

研究人员因手背静脉生物识别（dorsal hand vein biometrics）所具备的独特特性，对其关注度与日俱增。其核心特性可归纳如下：无需与采集设备接触、难以被伪造、不会随时间发生变化，且识别精度较高。手背静脉识别系统的性能优劣，取决于设备采集到的图像质量。研究人员借助近红外（NIR）光线实现手背静脉与周围组织的区分成像。
本研究提出的非接触式硬件系统用于图像采集，该硬件由三部分组成：USB摄像头、红外发光二极管（infrared LEDs）以及智能手机。该USB摄像头分辨率为640×480像素，为使其对红外光线敏感，研究人员对其进行了改装：移除原有的红外截止滤镜，并加装了一层仅允许700nm以上波长光线通过的磁性薄膜滤镜。在照明模块方面，20个红外发光二极管被安装在测试电路板上，并连接至电源。手背由红外发光二极管进行照明，随后摄像头开始采集帧图像，并通过OTG（On-The-Go）数据线将图像传输至智能手机以进行后续处理。