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Analysis of pattern recognition and dimensionality reduction techniques for odor biometrics

机译：气味生物特征识别和降维技术的分析

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摘要

In this paper, we analyze the performance of several well-known pattern recognition and dimensionality reduction techniques when applied to mass-spectrometry data for odor biometric identification. Motivated by the successful results of previous works capturing the odor from other parts of the body, this work attempts to evaluate the feasibility of identifying people by the odor emanated from the hands. By formulating this task according to a machine learning scheme, the problem is identified with a small-sample-size supervised classification problem in which the input data is formed by mass spectrograms from the hand odor of 13 subjects captured in different sessions. The high dimensionality of the data makes it necessary to apply feature selection and extraction techniques together with a simple classifier in order to improve the generalization capabilities of the model. Our experimental results achieve recognition rates over 85% which reveals that there exists discriminatory information in the hand odor and points at body odor as a promising biometric identifier.
机译：在本文中，我们分析了几种著名的模式识别和降维技术在应用于质谱数据进行气味生物识别时的性能。由于先前的工作成功地捕获了人体其他部位的气味，因此这项工作试图评估通过从手上散发出的气味来识别人的可行性。通过根据机器学习方案制定此任务，可以用小样本规模监督分类问题来识别该问题，在该问题中，输入数据由质谱图形成，这些质谱图来自在不同时段捕获的13位受试者的手臭。数据的高维性使得有必要将特征选择和提取技术与简单的分类器一起使用，以提高模型的泛化能力。我们的实验结果达到了超过85％的识别率，这表明在手部气味中存在区分性信息，并指出体味是有希望的生物识别标志。

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  • 来源
    《Knowledge-Based Systems》 |2013年第11期|279-289|共11页
  • 作者

    Irene Rodriguez-Lujan; Gonzalo Bailador; Carmen Sanchez-Avila; Ana Herrero; Guillermo Vidal-de-Miguel;

  • 作者单位

    Centro de Domotica Integral (CeDInt-UPM),Universidad Politecnica de Madrid, Campus de Montegancedo, 28223 Pozuelo de Alarcon, Madrid, Spain BioCircuits Institute, University of California San Diego, San Diego, CA, USA;

    Centro de Domotica Integral (CeDInt-UPM),Universidad Politecnica de Madrid, Campus de Montegancedo, 28223 Pozuelo de Alarcon, Madrid, Spain BioCircuits Institute, University of California San Diego, San Diego, CA, USA;

    Centro de Domotica Integral (CeDInt-UPM),Universidad Politecnica de Madrid, Campus de Montegancedo, 28223 Pozuelo de Alarcon, Madrid, Spain BioCircuits Institute, University of California San Diego, San Diego, CA, USA;

    SEADM S.L., Valladolid, Spain;

    SEADM S.L., Valladolid, Spain;

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  • 正文语种 eng
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  • 关键词

    Biometrics; Odor; Supervised classification; Feature selection; Mass-spectrometry;

    机译：生物识别;气味;监督分类;功能选择;质谱;

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