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首页> 外文学位 >Automatic features identification with Infrared Thermography in Fever Screening.
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Automatic features identification with Infrared Thermography in Fever Screening.

机译：发热筛查中的红外热成像自动识别功能。

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摘要

The goal of this thesis is to develop an algorithm to process infrared images and achieve automatic identification of moving subjects with fever. The identification is based on two main features: the distinction between the geometry of a human face and other objects in the field of view of the camera, and the temperature of the radiating object. Infrared thermography is a remote sensing technique used to measure temperatures based on emitted infrared radiation. Applications include fever screening in major public places such as airports and hospitals. Current accepted practice of screening requires people to stay in a line and temperature measurements are carried out for one person at a time. However in the case of mass screening of moving people the accuracy of the measurements is still under investigation.;An algorithm constituting of image processing to threshold objects based on the temperature, template matching and hypothesis testing is proposed to achieve automatic identification of fever subjects. The algorithm was first tested on training data to obtain a threshold value (used to discriminate between face and non face shapes) corresponding to a false detection rate of 5%, which in turn corresponds to 85% probability of detection using Neyman-Pearson criterion.;By testing the algorithm on several simulated and experimental images (which reflect relevant scenarios characterizing crowded places) it is observed that it can be beneficially implemented to introduce automation in the process of detecting moving subjects with fever.
机译：本文的目的是开发一种处理红外图像并自动识别发烧运动对象的算法。识别基于两个主要特征：在照相机视场中人脸和其他物体的几何形状之间的区别，以及辐射物体的温度。红外热成像技术是一种遥感技术，用于根据发出的红外辐射测量温度。应用包括在机场和医院等主要公共场所进行发烧筛查。当前公认的筛查方法要求人们排成一列，并且一次只能对一个人进行温度测量。然而，在对人群进行大规模筛查的情况下，测量的准确性仍在研究中。提出了一种基于温度，模板匹配和假设检验的图像处理阈值对象的算法，以实现发烧对象的自动识别。首先在训练数据上对该算法进行测试，以获得一个阈值（用于区分面部和非面部形状），该阈值对应于5％的错误检测率，这相应地对应于使用Neyman-Pearson准则的85％的检测概率。 ；通过在数个模拟和实验图像（反映反映拥挤场所特征的相关场景）上测试该算法，可以观察到该算法可以被有利地实现，以在检测发烧的运动对象的过程中引入自动化。

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  • 作者

    Surabhi, Vijaykumar.;

  • 作者单位

    University of Ottawa (Canada).;

  • 授予单位 University of Ottawa (Canada).;
  • 学科 Engineering Biomedical.;Engineering Automotive.
  • 学位 M.A.Sc.
  • 年度 2012
  • 页码 81 p.
  • 总页数 81
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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