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Analysis of Pulsed Thermographic Sequences based on Radon Transform

机译:基于Radon变换的脉冲热成像序列分析

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The automatic detection of subsurface defects has become a desired goal in the application of Non Destructive Techniques. In this paper, a new algorithm based on the Radon Transform is proposed to reduce human intervention to a minimum in the field of Thermography for defect detection and/or characterization. The analysis of a thermographic sequence for the detection of subsurface defects can be reduced to the identification of the -0.5 slope in the surface temperature decay for each pixel within the image. Employing techniques commonly used in computer vision, an algorithm can be developed in order to look for the -0.5 slope in the temporal temperature decay profiles of each pixel. In our case, the Radon transform can be used to detect those -0.5 slope lines in the temporal temperature decay profiles. The final result provided by this algorithm is an image showing the different defects avoiding the necessity of evaluating parameters as relevant in other algorithms as the delayed time of the first image or any subjective point of view in the analysis. All the information is contained in only one image and leads to a quantitative estimation of the defect depths. The principal limitation is that the specimens under inspection should be semi-infinite homogeneous samples because this algorithm is supported on a 1-D Fourier diffusion equation approximation. Experimental works using a Plexiglas™ specimen were performed showing a good agreement with other semi-automated techniques.
机译:在无损检测技术的应用中,表面缺陷的自动检测已成为期望的目标。在本文中,提出了一种基于Radon变换的新算法,可以将热成像领域的人为干预降至最低,以进行缺陷检测和/或表征。用于检测亚表面缺陷的热成像序列分析可以简化为识别图像中每个像素的表面温度衰减的-0.5斜率。利用计算机视觉中常用的技术,可以开发一种算法,以便在每个像素的时间温度衰减曲线中寻找-0.5斜率。在我们的情况下,Radon变换可用于检测时间温度衰减曲线中的-0.5斜线。该算法提供的最终结果是一幅图像,显示了不同的缺陷,从而避免了评估与其他算法(如第一幅图像的延迟时间或分析中的任何主观观点)相关的参数的必要性。所有信息仅包含在一张图像中,并导致对缺陷深度的定量估计。主要限制在于,被检查的样本应该是半无限均匀的样本,因为该算法在一维傅立叶扩散方程近似中得到支持。使用Plexiglas™标本进行的实验工作与其他半自动化技术显示出良好的一致性。

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