Defect extraction and segmentation automatically in x-ray images of carbon material
炭素制品x射线图像缺陷的自动提取与分割

Regarding the characteristic of X-ray detection images of carbon produce, defect extraction techniques were studied with target boundary extraction algorithm and image enhancement algorithm based on wavelet, background removal and enhancement of object region were implemented successfully. Based on this, there had two ways to recognize different type of defect: firstly, wavelet transforms was introduced to extract defect edge, secondly, mathematical morphology linking iteration threshold was adopted to extract defect area. The experimental results indicate that both of methods can achieve defect extraction and segmentation automatically, which will lay a good foundation for flaw feature parameter extraction.