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Design and analysis of a biometric access control system using an electronic olfactory device to identify human odour characteristics

机译:使用电子嗅觉设备识别人的气味特征的生物特征访问控制系统的设计和分析

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摘要

The use of an electronic olfactory device, termed an electronic 'nose', was investigated for the detection of unique human odour characteristics. The detection of these unique odours was applied to the field of biometrics for access control, where a human's unique characteristics were used to authenticate a user of an access control system. An electronic odour sensing device was designed and constructed using an array of conducting polymer gas sensors in order to facilitate the regular screening of a group of human subjects over a period of six weeks.ududA static sampling method was used to measure odour levels from human hands, which were found to contain a reliable source of human odour. Human odour levels were low so dynamic sampling proved to be unsuitable for this application due to the dilution of the odour mixture. Feature analysis results revealed that the features of adsorption and desorption gradient contained discriminatory information in addition to the commonly used maximum divergence. Pattern recognition revealed that neural network architectures produced superior results when compared to statistical methods as a result of their ability to model the non-linearities in the data set. The highest recognition rate was 73% which was produced using a Multi-Layer Perceptron (MLP) neural network compared to 63% obtained using the best statistical method of Parzen windows. The majority of the recognition error was caused by a minority of the humans. Analysis of sensor data revealed that only 30% of the sensor array were contributing discriminatory information so it was deduced that performance would undoubtedly improve if a full array of effective sensors were available.ududExploratory data analysis revealed that human odour changed from day to day and often an increasing divergence with time was observed. A time-adaptive method was devised which increased the recognition to 89%, but was still too low for use as a biometric recognition device. However, use as a verification device demonstrated acceptable levels of performance but resulted in high levels of user frustration caused by a high proportion of users being falsely rejected. This work demonstrated that an olfactory based biometric access control system could be a realistic proposition but requires further work, especially in the areas of sensor development and unique human odour research, before an operational system could be produced.
机译:为了检测独特的人类气味特征,研究了使用电子嗅觉装置(称为电子“鼻子”)的方法。这些独特气味的检测被应用于访问控制的生物识别领域,其中人类的独特特征被用来验证访问控制系统的用户。设计了一种电子气味感应设备,该设备使用一系列导电聚合物气体传感器进行设计和构造,以便于在六周的时间内定期筛查一组人类受试者。 ud ud使用静态采样方法测量气味水平来自人的手,被发现含有可靠的人味。人的气味水平很低,因此由于稀释了气味混合物,因此动态采样证明不适合此应用。特征分析结果表明,吸附和解吸梯度的特征除常用的最大散度外还包含歧视性信息。模式识别表明,与统计方法相比,神经网络体系结构具有建模数据集中非线性的能力,因此产生了优异的结果。使用多层感知器(MLP)神经网络产生的最高识别率为73%,而使用最佳Parzen窗口统计方法获得的识别率为63%。大部分识别错误是由少数人引起的。对传感器数据的分析表明,只有30%的传感器阵列提供了歧视性信息,因此可以推断出,如果有完整的有效传感器阵列,性能无疑会提高。 ud ud探索性数据分析表明,人类的气味每天都在变化。白天,并且通常观察到随着时间的推移,差异越来越大。设计了一种时间自适应方法,该方法将识别率提高到89%,但是对于用作生物识别器来说仍然太低了。然而,用作验证设备证明了可接受的性能水平,但是由于高比例的用户被错误拒绝而导致高水平的用户挫败感。这项工作表明,基于嗅觉的生物特征访问控制系统可能是一个现实的主张,但需要进一步的工作,特别是在传感器开发和独特的人类气味研究领域,才能生产出操作系统。

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    McMillan Stephen;

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  • 年度 2000
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  • 原文格式 PDF
  • 正文语种 en
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