Abstract
At present, several methods are being evolved in enhancing probability of detection (POD) in the domain of Non-destructive Testing (NDT). However there is demand for reducing human exhaustion and enhance POD in NDT due to lack of accuracy and time to complete the detection and interpretation of defects..To improve this process, an attempt towards incorporating several computational techniques is being analyzed. Yet, a robust model incorporating suitable image processing techniques and an efficient interpretation mechanism with an appropriate visualization technique is proposed. The system attempts to process the radiographs to segregate and extract the different Region of Interest (ROI) s (defects) from the given image using an automated task. For image classification, Convolutional Neural Network (CNN) is used. Thus, a complete AI based computational solution is devised for processing, interpreting the radiographic weld defects.
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