Detection of Weld Defects in Radiography Films Using Image Processing
Abstract. Todays, the range of applications of image processing in various fields such as medical, robotics, agriculture and meteorology spread. Several studies have been conducted in these areas, but little researches have been done regarding its application in weld inspection. To test the groove and complete joint penetrating high-strength welding defects (such as pressure vessels, heat boilers, etc.) used radiography testing method. In the case of defects that are similar but have different acceptance criteria, minimize or eliminate the errors in radiography films by optimizing images using image processing. In image processing, edge detection, improving image quality and accurate color diagnosis is possible and help to accurately identifying of defects and decreases errors in diagnosis of defects type. In this study, the method for detection of internal defects of weld in radiography films using image processing will be investigated that its results can be used to eliminate the need for human interpretation of film and fully automate it using a machine.so first the general and basic concepts related to image processing, as well as a variety of weld defects will be described, then, using the results of research and development, effective way to identify defects using image processing algorithms will be provided and implement procedures and methods of it, using MATLAB software will be explained.
Marcelo Kleber Felisberto, Heitor Silvério Lopes, Tania Mezzadri Centeno, (2006) ”An object detection and recognition system for weld bead extraction from digital radiographs”, Computer Vision and Image Understanding, Volume 102, Issue 3, Pages 238-249
Remi Cogranne, (2014) “Statistical detection of defects in radiographic images using an adaptive parametric model”, Signal Processing, Volume 96, Part B, Pages 173–189
Romeu R. da Silva, Luiz P. Calôba, Marcio H.S. Siqueira, (2004) “Pattern recognition of weld defects detected by radiographic test”, NDT & E International, Volume 37, Issue 6.
Q. He, (1999) "A Review of Clustering Algorithms as Applied in IR", Graduate School of Library and Information Science University of Illinois at Urbana-Champaign.