Defect detection method based on 2D entropy image segmentation

In order to improve the work efficiency of non-destructive testing (NDT) and the reliability of NDT results, an automatic method to detect defects in the ultrasonic image was researched. According to the characterization of ultrasonic D-scan image, clutter wave suppression and de-noising were presented firstly. Then, the image is processed by binaryzation using KSW 2D entropy based on image segmentation method. The results showed that, the global threshold based segmentation method was somewhat ineffective for D-scan image because of under-segmentation. Especially, when the image is big in size, small targets which are composed by a small amount of pixels are often undetected. Whereas, local threshold based image segmentation method is effective in recognizing small defects because it takes local image character into account.