LAUSR

Radiography testing (RT) is a well-established non-destructive method for the detection and measurement of defects in the welded objects. Unfortunately, however, the image quality of radiographs is often low mainly due to the unavoidable detection of scattered X-rays. This superimposed noise on the images could result in low detectability and inaccurate dimensional measurement of such defects. Application of image processing solutions has found wide application since hardware-based removal of the noise is often impractical. The Chambolle algorithm is a method for minimizing the total statistical variance within an image which is fast and efficient and is based on a projection-based algorithm. The enhanced images processed through the Chambolle method have significantly improved contrasts and yield higher accuracy for defect dimensional measurements when compared to original images. In this study, the Chambolle algorithm was used to increase the contrast in the defect regions of the radiographs of ‘Sonaspection kit’ objects where contrast enhancements by up to a factor of about 3.5 were obtained. Also, dimensions of standard defects from the ‘Sonaspection kit” were measured to an accuracy of better than 5% using images from the processed images compared to inaccuracies of about 15% when original radiographs of the same defect were analyzed.