Biometric recognition systems based on ultrasonic images have several advantages over other technologies, including the capability of capturing 3D images and detecting liveness. In this work, a recognition system based on hand geometry achieved through ultrasound images is proposed and experimentally evaluated. 3D images of human hand are acquired by performing parallel mechanical scans with a commercial ultrasound probe. Several 2D images are then extracted at increasing under-skin depths and, from each of them, up to 26 distances among key points of the hand are defined and computed to achieve a 2D template. A 3D template is then obtained by combining in several ways 2D templates of two or more images. A preliminary evaluation of the system is achieved by carrying out verification experiments on a home-made database. Results have shown a good recognition accuracy: the Equal Error Rate was 1.15% when a single 2D image is used and improved to 0.98% by using the 3D template. The possibility to upgrade the proposed system to a multimodal system, by extracting from the same volume other features like palmprint and hand veins, as well as possible improvements are finally discussed.

中文翻译：

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通过 3D 超声手部几何体进行生物识别

基于超声波图像的生物识别系统与其他技术相比具有多项优势，包括捕获 3D 图像和检测活体的能力。在这项工作中，提出了一种基于通过超声图像实现的手部几何形状的识别系统，并进行了实验评估。人手的 3D 图像是通过使用商用超声探头执行并行机械扫描来获取的。然后以增加的皮下深度提取多个 2D 图像，并从每个图像中定义和计算手部关键点之间多达 26 个距离以实现 2D 模板。然后通过以多种方式组合两个或多个图像的 2D 模板来获得 3D 模板。通过在自制数据库上进行验证实验，对系统进行初步评估。结果显示了良好的识别准确率：使用单个 2D 图像时的等错误率为 1.15%，使用 3D 模板提高到 0.98%。最后讨论了通过从同一体积中提取其他特征（如掌纹和手静脉）以及可能的改进来将所提出的系统升级为多模态系统的可能性。