X ray imaging has many problems such as noise, penumbra and scattering, which results in blurred edge of the image and the uneven background gray level and seriously affects the accuracy of defect identification. We propose a new defect detection method for Xray images based on LoG edge detection and local contrast to carry out saliency discrimination. On the basis of the salient edge detection based on the double thresholds of LoG edge detection, the local background of undetermined defects is obtained by the isotropic diffusion method. We also set a third threshold by utilizing the contrast saliency between undetermined defects and the local background to remove the false defects, so that the defects can be accurately extracted and the contour and area of defects can be determined at the same time. Experimental results show that the algorithm has high accuracy for defect identification and can be used for online real-time detection systems.