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首页> 外文期刊>Arabian Journal for Science and Engineering >Multimodal Biometric Systems: A Comparative Study
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Multimodal Biometric Systems: A Comparative Study

机译：多峰生物识别系统：比较研究

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摘要

Biometrics technology stands as one of the major backbones that had united biosciences and technology representing an instrument for security and forensics researchers to develop more accurate, robust and confident systems. Starting from uni-modal biometrics as finger print, face, speech and iris passing through multimodal biometrics based on uni-biometrics fused by different fusion techniques as feature level, score level and decision level fusion techniques, biometrics were still one of the most investigated technologies. From here in this paper, we tried to build the base for researchers whom are interested in biometric systems through introducing a comparative study of most used and known uni- and multimodal biometrics such as face, iris, finger vein, face and iris multimodal, face, finger print and finger vein multimodal. Through this comparative study, a comparative model is based on principal component analysis feature extractor and Euclidean distance matcher applied using MATLAB. This model was trained and tested in two different modes homogenous data using SDUMLA-HMT database and heterogeneous mode extracting 106 frontal single face image from CASIA-FACEV5 while the reminder biometrics under consideration from SDUMLA-HMT. Feature level and score level fusions were tested in both modes on all multimodal systems under consideration.
机译：生物识别技术是将生物科学与技术结合在一起的主要支柱之一，代表着安全和法医研究人员开发更准确，健壮和自信的系统的工具。从指纹，面部表情，语音和虹膜等单峰生物特征开始，经过基于单峰生物特征的多峰生物特征，这些特征通过不同的融合技术（例如特征水平，得分水平和决策水平融合技术）融合在一起，生物特征仍然是研究最多的技术之一。从本文的此处，我们试图通过引入对最常用和已知的单峰和多峰生物特征（例如面部，虹膜，手指静脉，面部和虹膜多峰，面部）进行比较研究，为对生物识别系统感兴趣的研究人员建立基础。 ，指纹和手指静脉多式联运。通过比较研究，建立了一个基于主成分分析特征提取器和使用MATLAB的欧氏距离匹配器的比较模型。使用SDUMLA-HMT数据库以两种不同模式的同质数据对模型进行了训练和测试，并通过异构模式从CASIA-FACEV5提取了106张正面单脸图像，同时考虑了SDUMLA-HMT的提醒生物特征。在考虑中的所有多模式系统上，都以两种模式测试了特征级别和得分级别融合。

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