Abstract
Traditionally, the inspection of welding defects through X-rays is being carried out by experienced inspectors having sharp vision and adequate knowledge in identifying the defects. The inspection by human experts may sometimes lead to misinterpretation and found to be time-consuming. Hence, to increase the objectivity, accuracy, consistency and efficiency of radiographic image inspection, fully automated systems have been proposed by many researchers. Further image processing plays a vital role in the process of defect detection and classification in these automated systems. This paper focuses on the survey of existing image processing methods of radiographic testing to recognise and classify the defective patterns.
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