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Locating Geometrical Descriptors for Hand Biometrics in a Contactless Environment

机译:在非接触式环境中定位用于手工生物识别的几何描述符

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This paper proposes an innovative contactless hand geometry recognition system. We present a novel hand tracking approach to automatically detect and capture the geometrical features of the hand from low resolution video stream. No constraint is imposed and the subject can place his/her hand naturally on top of the sensor without touching any device. Conventional hand geometry systems require fairly precise positioning of the hand in order to obtain accurate measures of the hand. However, the proposed contactless approach does not fix any guidance pegs to help placing the hand at the right position when the image is acquired. As a result, the hand image may appear larger when the hand is placed near the sensor, and vice versa. Besides, the hand can be positioned at different angles. In other words, there is no way to obtain standard and constant hand measurements from this contactless setting. This research aims to deal with this complication when we have to get accurate measurements of the hand from images with varying sizes and directed at different orientations. Experiments show that our proposed method offers promising result for hand geometry recognition in a real-time contactless environment.
机译:本文提出了一种创新的非接触式手工几何识别系统。我们提出了一种新颖的手动跟踪方法,可以从低分辨率视频流自动检测和捕获手的几何特征。没有施加约束,并且受试者可以自然地将他/她的手放在传感器的顶部,而不会触摸任何装置。传统的手几何系统需要相当精确定位手动以获得准确的手测量。然而,所提出的非接触式方法不会修复任何引导栓,以帮助在获取图像时将手放在正确位置。结果,当手放置在传感器附近时,手图像可能会较大,反之亦然。此外,手可以以不同的角度定位。换句话说,没有办法从该非接触式设置中获得标准和常量的手动测量。该研究旨在处理这种并发症,当我们必须从具有不同尺寸的图像准确测量手,并以不同的方向指导。实验表明,我们的建议方法在实时非接触环境中提供了手部几何识别的有希望的结果。

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