Evaluating the performance of various segmentation techniques in industrial radiographs

At present, image processing concepts are widely used in different fields, such as remote sensing, communication, medical imaging, forensics and industrial inspection. Image segmentation is one of the key processes in image processing key stages. Segmentation is a process of extracting various features of the image which can be merged or split to build the object of interest, on which image analysis and interpretation can be performed. Many researchers have proposed various segmentation algorithms to extract the region of interest from an image in various domains. Each segmentation algorithm has its own pros and cons based on the nature of the image and its quality. Especially, extracting a region of interest from a gray scale image is incredibly complex compared to colour images. This paper attempts to perform a study of various widely used segmentation techniques in gray scale images, mostly in industrial radiographic images that would help the process of defects detection in non-destructive testing.