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首页> 外文期刊>Optical engineering >Palmprint and face score level fusion: hardware implementation of a contactless small sample biometric system
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Palmprint and face score level fusion: hardware implementation of a contactless small sample biometric system

机译：掌纹和面部分数级别融合：非接触式小样本生物识别系统的硬件实现

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摘要

Including multiple sources of information in personal identity recognition and verification gives the opportunity to greatly improve performance. We propose a contactless biometric system that combines two modalities: palmprint and face. Hardware implementations are proposed on the Texas Instrument Digital Signal Processor and Xilinx Field-Programmable Gate Array (FPGA) platforms. The algorithmic chain consists of a preprocessing (which includes palm extraction from hand images), Gabor feature extraction, comparison by Hamming distance, and score fusion. Fusion possibilities are discussed and tested first using a bimodal database of 130 subjects that we designed (uB database), and then two common public biometric databases (AR for face and PolyU for palmprint). High performance has been obtained for recognition and verification purpose: a recognition rate of 97.49% with AR-PolyU database and an equal error rate of 1.10% on the uB database using only two training samples per subject have been obtained. Hardware results demonstrate that preprocessing can easily be performed during the acquisition phase, and multimodal biometric recognition can be treated almost instantly (0.4 ms on FPGA). We show the feasibility of a robust and efficient multimodal hardware biometric system that offers several advantages, such as user-friendliness and flexibility.
机译：在个人身份识别和验证中包含多种信息源可大大改善性能。我们提出了一种非接触式生物识别系统，该系统结合了两种模式：掌纹和面部。在德州仪器数字信号处理器和赛灵思现场可编程门阵列（FPGA）平台上提出了硬件实现方案。该算法链包括预处理（包括从手图像中提取手掌），Gabor特征提取，通过汉明距离进行比较以及分数融合。首先使用我们设计的130个受试者的双峰数据库（uB数据库），然后使用两个常见的公共生物特征数据库（用于面部的AR和用于手掌的PolyU）来讨论和测试融合的可能性。出于识别和验证目的，已经获得了高性能：使用AR-PolyU数据库的识别率达到97.49％，在uB数据库上使用每个对象仅使用两个训练样本就获得的错误率达到1.10％。硬件结果表明，可以在采集阶段轻松进行预处理，并且几乎可以立即处理多模态生物特征识别（在FPGA上为0.4 ms）。我们展示了强大而有效的多模式硬件生物特征识别系统的可行性，该系统具有多个优点，例如用户友好性和灵活性。

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