An Examination of Computer Graphics and Image Technology’s Role in the Components of Visual Communication Design

In the big data era, design is gradually moving towards a new kind of intelligence. The use of algorithms to help designers complete time-consuming repetitive design tasks is one of the main tenets of the current generation of intelligent design research. This study initially uses the three-primary concept to create a set of vector functions in order to precisely measure error distances and create a partitioning model for visual communication. Second, in order to obtain the parameters for visual communication, the scientific encoding of the coefficient constraint features is accomplished, and the relevant hyper-plane is found by carefully extracting the feature information associated to the graphic image. In the end, the BCE With Logits technique can substantially improve the visual communication image represen-tation. The experimental results show that the modified BCE With Logits visual communication design model can be applied to four different types of images with different levels of tedium, and that when the weight parameter is set to 0.34, the accuracy of image recognition rises to 89.59\%, resulting in suc-cessful visual communication.