Automatic Thinning Detection through Image Segmentation Using Equivalent Array-Type Lamp-Based Lock-in Thermography.

Sensors (Basel)

Department of Future Convergence Engineering, Kongju National University, 1223-24 Cheonan-Daero, Seobuk-gu, Cheonan-si 31080, Republic of Korea.

Published: January 2023

Among the non-destructive testing (NDT) techniques, infrared thermography (IRT) is an attractive and highly reliable technology that can measure the thermal response of a wide area in real-time. In this study, thinning defects in S275 specimens were detected using lock-in thermography (LIT). After acquiring phase and amplitude images using four-point signal processing, the optimal excitation frequency was calculated. After segmentation was performed on each defect area, binarization was performed using the Otsu algorithm. For automated detection, the boundary tracking algorithm was used. The number of pixels was calculated and the detectability using RMSE was evaluated. Clarification of defective objects using image segmentation detectability evaluation technique using RMSE was presented.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9921815PMC
http://dx.doi.org/10.3390/s23031281DOI Listing

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