مشخصات پژوهش

عنوان	Using Interpolation with Nonlocal Autoregressive Modeling for Defect Detection in Welded Objects
نوع پژوهش	مقاله چاپ‌شده در مجلات علمی
کلیدواژه‌ها	Welded objects, Industrial radiography, Defects, Nonlocal autoregressive model, Sparse representation models
چکیده	X-rays and gamma rays are used in industrial radiography to detect internal defects and diferent structures of the test object. The radiography interpreters must be able to evaluate and interpret the radiography images as accurately as possible. To improve the operator’s image perception and interpretation, the quality of radiographs can be enhanced by diferent image processing methods. In this study, the sparse representation method with a nonlocal autoregressive model (NAM) based on a sparse representation model (SRM) algorithm was implemented to improve the defect detection capabilities. The technique relies on generating a regularized and smoothed image, which is then subtracted from the original image to reconstruct the high contrast image. The algorithm was successfully applied to diferent radiography images. Improved defect detection was achieved while preserving the fne details and the main information of the images. For the enhanced images of samples in this study, fgures of merits were found between 83 and 98% for the diferent defects and regions of interests in the reconstructed radiographs by the NAM–SRM algorithms. These fgures of merit were between 67 and 89% in the original radiographs, respectively. The results show that the reconstructed images by NARM–SRM algorithms have better visualization and also the defect regions are very clear to the original radiographs. Regarding computing time, the proposed method is faster than the other four chosen iterative methods.
پژوهشگران	امیر موافقی (نفر اول)، مهدی میرزاپور (نفر دوم)، عفت یاحقی (نفر سوم)