Multi-resolution analysis for region of interest extraction in thermographic nondestructive evaluation

B. Ortiz-Jaramillo; H. A. Fandiño Toro; H. D. Benitez-Restrepo; S. A. Orjuela-Vargas; G. Castellanos-Domínguez; W. Philips

doi:10.1117/12.912079

2 February 2012 Multi-resolution analysis for region of interest extraction in thermographic nondestructive evaluation

B. Ortiz-Jaramillo, H. A. Fandiño Toro, H. D. Benitez-Restrepo, S. A. Orjuela-Vargas, G. Castellanos-Domínguez, W. Philips

Author Affiliations +

Proceedings Volume 8295, Image Processing: Algorithms and Systems X; and Parallel Processing for Imaging Applications II; 82951J (2012) https://doi.org/10.1117/12.912079
Event: IS&T/SPIE Electronic Imaging, 2012, Burlingame, California, United States

Abstract

Infrared Non-Destructive Testing (INDT) is known as an effective and rapid method for nondestructive inspection. It can detect a broad range of near-surface structuring flaws in metallic and composite components. Those flaws are modeled as a smooth contour centered at peaks of stored thermal energy, termed Regions of Interest (ROI). Dedicated methodologies must detect the presence of those ROIs. In this paper, we present a methodology for ROI extraction in INDT tasks. The methodology deals with the difficulties due to the non-uniform heating. The non-uniform heating affects low spatial/frequencies and hinders the detection of relevant points in the image. In this paper, a methodology for ROI extraction in INDT using multi-resolution analysis is proposed, which is robust to ROI low contrast and non-uniform heating. The former methodology includes local correlation, Gaussian scale analysis and local edge detection. In this methodology local correlation between image and Gaussian window provides interest points related to ROIs. We use a Gaussian window because thermal behavior is well modeled by Gaussian smooth contours. Also, the Gaussian scale is used to analyze details in the image using multi-resolution analysis avoiding low contrast, non-uniform heating and selection of the Gaussian window size. Finally, local edge detection is used to provide a good estimation of the boundaries in the ROI. Thus, we provide a methodology for ROI extraction based on multi-resolution analysis that is better or equal compared with the other dedicate algorithms proposed in the state of art.

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B. Ortiz-Jaramillo, H. A. Fandiño Toro, H. D. Benitez-Restrepo, S. A. Orjuela-Vargas, G. Castellanos-Domínguez, and W. Philips "Multi-resolution analysis for region of interest extraction in thermographic nondestructive evaluation", Proc. SPIE 8295, Image Processing: Algorithms and Systems X; and Parallel Processing for Imaging Applications II, 82951J (2 February 2012); https://doi.org/10.1117/12.912079

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