For the inpainting of the images of textile cultural relics at the damaged parts, an improved algorithm is pro-posed based on K-means color segmentation and Criminisi algorithm. Due to the characteristics of textile cultural relics images, RGB images were converted into Lab color model, and K-means classifier was used to segment a* and b * layer data according to their colors to calibrate the edges of the patterns and narrow the search area of matching blocks. The standard deviation of L value was introduced to represent the color dispersion and the priority function and adaptive matching block were improved.The proposed algorithm and the three algorithms reported in the literature were used to repair the image of natural damaged textile relics and man-made damaged textile images, and the restoration results were evaluated. The experimental results show that the image restored by the proposed algorithm has natural texture, reasonable structure, and better peak signal-to-noise ratio, structural similarity, feature similarity, mean square error values.