TY - JFULL AU - Nafa芒 Nacereddine and Latifa Hamami and Djemel Ziou PY - 2007/8/ TI - Image Thresholding for Weld Defect Extraction in Industrial Radiographic Testing T2 - International Journal of Computer and Information Engineering SP - 2032 EP - 2041 VL - 1 SN - 1307-6892 UR - https://publications.waset.org/pdf/12939 PU - World Academy of Science, Engineering and Technology NX - Open Science Index 7, 2007 N2 - In non destructive testing by radiography, a perfect knowledge of the weld defect shape is an essential step to appreciate the quality of the weld and make decision on its acceptability or rejection. Because of the complex nature of the considered images, and in order that the detected defect region represents the most accurately possible the real defect, the choice of thresholding methods must be done judiciously. In this paper, performance criteria are used to conduct a comparative study of thresholding methods based on gray level histogram, 2-D histogram and locally adaptive approach for weld defect extraction in radiographic images. ER -