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Infrared-visible image registration for augmented reality-based thermographic building diagnostics

机译:红外可见图像配准,用于基于增强现实的热成像建筑诊断

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Background In virtue of their capability to measure temperature, thermal infrared cameras have been widely used in building diagnostics for detecting heat loss, air leakage, water damage etc. However, the lack of visual details in thermal infrared images makes the complement of visible images a necessity. Therefore, it is often useful to register images of these two modalities for further inspection of architectures. Augmented reality (AR) technology, which supplements the real world with virtual objects, offers an ideal tool for presenting the combined results of thermal infrared and visible images. This paper addresses the problem of registering thermal infrared and visible fa?ade images, which is essential towards developing an AR-based building diagnostics application. Methods A novel quadrilateral feature is devised for this task, which models the shapes of commonly present fa?ade elements, such as windows. The features result from grouping edge line segments with the help of image perspective information, namely, vanishing points. Our method adopts a forward selection algorithm to determine feature correspondences needed for estimating the transformation model. During the formation of the feature correspondence set, the correctness of selected feature correspondences at each step is verified by the quality of the resulting registration, which is based on the ratio of areas between the transformed features and the reference features. Results and conclusions Quantitative evaluation of our method shows that registration errors are lower than errors reported in similar studies and registration performance is usable for most tasks in thermographic inspection of building fa?ades.
机译:背景技术红外热像仪由于具有测量温度的能力,已被广泛用于建筑物诊断中,以检测热损失,空气泄漏,水损坏等。但是,由于红外热像仪中缺少视觉细节,使得可见光图像的补充成为可能。必要性。因此,注册这两种方式的图像对于进一步检查体系结构通常很有用。增强现实(AR)技术通过虚拟对象补充了现实世界,它是一种理想的工具,可用于显示热红外和可见图像的组合结果。本文解决了注册热红外图像和可见褪色图像的问题,这对于开发基于AR的建筑诊断应用程序至关重要。方法为此目的设计了一种新颖的四边形特征,该特征可以对常见的外观元素(例如窗户)的形状进行建模。这些特征是借助图像透视信息(即消失点)将边缘线段分组而得出的。我们的方法采用前向选择算法来确定估计转换模型所需的特征对应关系。在特征对应集的形成过程中,每个步骤中所选特征对应的正确性都由生成的配准的质量来验证,该结果基于转换后的特征与参考特征之间的面积比。结果与结论对我们方法的定量评估表明,配准误差低于类似研究中报告的误差,配准性能可用于建筑立面的热成像检查中的大多数任务。

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