The comparison and ranking of advanced data processing techniques of thermographic nonde-structive testing (NDT) seems decisive for end users who are required to optimize their NDT tools. This is a difficult task, which explains why there are so few articles dealing with this challenge. Furthermore, these works are often incomplete, since the choice of metrics is too limited and/or inappropriate to an accurate, unbiased ranking. Most of them are based on the number of detected discontinuities among a series of discontinuities of various sizes and depths, and the only assessed metric is the contrast-to-noise ratio of the disconti-nuity signatures. This observation justifies the need for a more thorough comparison, based on the evaluation of several unbiased parameters. In this article, three metrics are considered: not only the contrast-to-noise ratio, but also the sharpness of the discontinuity edges and the accuracy of the identified characteristic dimension of the discontinuity using the contrast full-width at half-maximum. They are assessed for a trio of thermal images of a composite sample with 12 embedded calibrated discontinuities, provided by four different pulse thermographic NDT data processing techniques: thermographic signal reconstruction polynomial coefficient (PC-TSR) technique, pulse phase thermography (PPT), principal component thermography (PCT), and higher order statistics (HOS). The relative compar-ison of the relevance of each of these techniques is then based on 432 discontinuity signatures (4 techniques × 3 images × 12 discontinuities × 3 metrics). In order to simplify the final ranking procedure, it is also shown that this high number of data can be drastically reduced to four numbers.
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