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利用近红外成像的多波长生物特征采集系统。

Multi-Wavelength Biometric Acquisition System Utilizing Finger Vasculature NIR Imaging.

机构信息

Faculty of Automatic Control, Electronics and Computer Science, Silesian University of Technology, Akademicka 16, 44-100 Gliwice, Poland.

Instituto de Astronomía, Universidad Nacional Autónoma de México (UNAM), Ciudad Universitaria, Mexico City 04510, Mexico.

出版信息

Sensors (Basel). 2023 Feb 10;23(4):1981. doi: 10.3390/s23041981.

Abstract

Personal identification using analysis of the internal and external characteristics of the human finger is currently an intensively developed topic. The work in this field concerns new methods of feature extraction and image analysis, mainly using modern artificial intelligence algorithms. However, the quality of the data and the way in which it is obtained determines equally the effectiveness of identification. In this article, we present a novel device for extracting vision data from the internal as well as external structures of the human finger. We use spatially selective backlight consisting of NIR diodes of three wavelengths. The fast image acquisition allows for insight into the pulse waveform. Thanks to the external illuminator, images of the skin folds of the finger are acquired as well. This rich collection of images is expected to significantly enhance identification capabilities using existing and future classic and AI-based computer vision techniques. Sample data from our device, before and after data processing, have been shared in a publicly available database.

摘要

利用人类手指的内外特征进行身份识别目前是一个研究热点。该领域的工作涉及到特征提取和图像分析的新方法,主要使用现代人工智能算法。然而,数据的质量及其获取方式同样决定了识别的有效性。在本文中,我们提出了一种从人手指的内外结构中提取视觉数据的新设备。我们使用由三个波长的近红外二极管组成的空间选择性背光源。快速的图像采集可以深入了解脉搏波形。由于外部照明器,还可以获取手指皮肤褶皱的图像。这些丰富的图像集有望使用现有的和未来的经典及基于人工智能的计算机视觉技术显著提高识别能力。我们在公共数据库中共享了设备的样本数据,包括处理前后的数据。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6751/9962154/696acb2535f7/sensors-23-01981-g001.jpg

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