Analysis of pulsed thermographic sequences based on radon transform

Abstract

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 PlexiglasTM specimen were performed showing a good agreement with other semi-automated techniques.