Traditional painting methods require a lot of time and energy, and their creative efficiency is low, making it difficult to meet the needs of modern and efficient life. With the development of technology, painting technology has been greatly improved, from manual painting to electronic painting, and now to intelligent processing technology for painting. Among these technologies, fuzzy logic control systems and computer image recognition technology play a crucial role. This paper analyzed a computer image recognition algorithm based on YOLOv3 (You Only Look Once version 3) algorithm, Mask R-CNN (Mask Region-based Convolutional Neural Network) algorithm and residual network network (ResNet) algorithm, as well as a fuzzy logic control system that can be used for automatic color filling, intelligent assisted painting and image enhancement, and analyzed the development of an intelligent painting tool by combining the fuzzy logic control system with computer image recognition technology. The experiment proved that the painting intelligent processing technology analyzed in this paper has better object recognition, object detection and object segmentation capabilities. The highest value of the creation process time of the painting works created using the painting intelligent processing technology analyzed in this paper was 499.92 minutes; the highest average line smoothness score was 133.484; the highest painting accuracy score was 138.36. In addition, most of the experimental participants gave positive feedback on the user experience. This technology can enhance the artistic value and aesthetic appeal of digital painting, providing artists with more creativity and inspiration. In summary, the intelligent painting processing technology based on computer vision and fuzzy logic control systems analyzed in this article could have a positive impact on the development of digital painting, and also provide new ideas and methods for research in related fields.