Image completion is a technique widely used that automatically removes objects or repairs damaged portions of image. However, information regarding the original image is often lacking in structure reconstruction, and as a result, images with complex structures are difficult to restore. This study proposed a support vector regression-oriented image completion (SVR-IC) method, the goal of which is to predict the original structure of unknown areas and then repair or make appropriate adjustments to the structure and texture of the damaged area. From the experimental results, SVR-IC produced images of good quality that were superior to those of other methods. The results show that integrated structure prediction to image completion can effectively enhance the quality of the restored image.