Abstract: In order to improve the automated recognition and segmentation in X-ray image of weld defects, an algorithm of X-ray image enhancement and segmentation based principal component analysis (PCA) was proposed. Firstly, the eigenvalue and its corresponding eigenvector of the image covariance matrix were calculated, according to the distribution of eigenvalue, the region of interest (ROI), just as weld, was located, the calculation capacity was reduced; Secondly, through analyzing the eigenvalue cumulative percentage and experimental results, the optimum eigenvector was selected to reconstruct the image based on PCA; Finally, the Otsu thresholding segmentation approach was employed to segment the reconstructed image. The results showed that this algorithm was effective in segmenting the X-ray image which was low contrast and noise severely.