Research on fusion generation algorithm of visual communication and product design based on AIGC technology - Guoying Chen; Xiaofeng Lan; Kai Liu; Can Cheng (Systems and Soft Computing)
The current field of visual communication and product design is faced with some problems, such as low efficiency of creative inspiration acquisition, cumbersome design process and difficult to meet personalized needs. This paper analyzes the application of AIGC technology in visual communication, including the key role of AIGC generation model in design and its methods to improve design efficiency. The application of AIGC technology in product design and its change to the traditional design process are discussed, and the automatic design generation method based on AIGC is emphatically introduced. The design of the combination of straight face and inclined face improves the visual hierarchy, making the overall design perception score reach 593 points, which is 38 points higher than the previous design, indicating that the visual optimization effect is remarkable. In the design scheme generated by AIGC technology, the uniformity of color and material is improved by 4.66 %, and the success rate of systematic optimization design is 5.2 %, further improving the consistency and visual appeal of the design. In this experiment, the perceptual characterization model is validated using 28 indicators, providing a robust data foundation for design improvement. This paper makes an in-depth analysis of the requirements of fusion of visual communication and product design, and puts forward the basic framework of fusion generation algorithm and the method of dynamic fusion of visual communication and product design elements based on convolutional neural network. Finally, the effectiveness and advantages of the proposed algorithm are verified by experimental analysis.