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Liveness Detection in Finger Vein Imaging Device Using Plethysmographic Signals

机译:使用体积素信号的手指静脉成像装置中的活性检测

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Finger vein modality is a relatively new area in biometrics that overcomes the limitations of biometric systems based on external features. Despite the fact that finger veins are invisible to naked eye and latent print doesn't exist, presentation attack on finger veins is possible if stored samples are stolen or compromised. To counter these attacks, liveness was ascertained using learning based methods. However, these methods are designed to detect only finger vein artefact generated using specific materials. Hardware based liveness detection methods make use of intrinsic characteristics of a live body to differentiate living tissues from artificially created materials resembling it. Thus hardware based liveness detection methods appear to be more robust to a wider class of spoofing attacks. In this paper, we propose a finger vein biometric device with a switchblade model sensor plate to ascertain the presence of a live finger. The blood flow pattern obtained from the sensor is hard to replicate and the presence of a physiological signal inherently implies liveness of the subject. The results after comparing quality of the vein images acquired from the proposed device and images from open databases show that the proposed device produces good quality images. The experimental results demonstrate that the developed prototype device with presentation attack detection (PAD) can successfully avert spoof attacks.
机译:手指静脉模态是生物识别结构中的相对较新的区域,克服了基于外部特征的生物识别系统的局限性。尽管手指静脉对肉眼看不见并不存在,但如果储存样品被盗或损害,则可以对手指静脉进行呈现攻击。为了反击这些攻击,使用基于学习的方法确定了活力。然而,这些方法旨在仅检测使用特定材料产生的手指静脉伪造。基于硬件的活性检测方法利用活体的内在特征,以区分从类似于它的人工创造的材料的生物组织。因此,基于硬件的活性检测方法对于更广泛的欺骗攻击似乎更加强大。在本文中,我们提出了一种手指静脉生物识别装置,具有切换模型传感器板来确定活手指的存在。从传感器获得的血流模式难以复制,并且生理信号的存在固有地意味着受试者的活力。结果在从开放数据库中获取的从所提出的设备和图像获取的静脉图像的质量之后,表明所提出的设备产生良好的质量图像。实验结果表明,具有呈现攻击检测(PAD)的开发的原型设备可以成功地避免欺骗攻击。

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