A new method for identifying people by their odor is proposed. In this approach, subjects are characterized by a GC × GC–MS chromatogram of a sample of their hand odor. The method is based on the definition of a distance between odor chromatograms and the application of Bayesian hypothesis testing. Using a calibration panel of subjects for whom several odor chromatograms are available, the densities of the distance between chromatograms of the same person, and between chromatograms of different persons are estimated. Given the distance between a reference and a query chromatogram, the Bayesian framework provides an estimate of the probability that the corresponding two odor samples come from the same person. We tested the method on a panel that is fully independent from the calibration panel, with promising results for forensic applications.

提出了一种通过气味识别人的新方法。通过这种方法，受试者的特征在于其手臭样品的GC×GC-MS色谱图。该方法基于气味色谱图之间距离的定义以及贝叶斯假设检验的应用。使用具有多个气味色谱图的对象的校准面板，可以估算同一个人的色谱图之间以及不同个人的色谱图之间的距离密度。给定参考色谱图和查询色谱图之间的距离，贝叶斯框架提供对相应的两个气味样品来自同一个人的概率的估计。我们在完全独立于校准面板的面板上测试了该方法，在法医学应用中获得了可喜的结果。