Абстрактный

SEGMENTATION OF RADIOGRAPHIC IMAGES OF WELD DEFECT

Wafaa Al-Hameed,Prof. Yahya Mayali and Prof. Phil Picton

The first stage in the classification or identification of defects in gray-level x-ray images of welds is the segmentation of the defects. The gray levels in weld images depend on the density and thickness of the material being tested. This causes the relative contrast of the defect area to vary with its position. As a consequence, it is difficult to carry out the process of segmentation. As a result, the subsequent stages of operations such as classification or recognition are affected. In this paper, different segmentation methods are introduced which are known as “data-driven”. In this approach, only the gray-level data is used to identify an area of interest, i.e. an area of the image that contains a defect, and hence extract it. The comparison of results show that using the morphology process with local thresholding yields better results than using edge detection method such as Sobel and Canny filters.