A Study of Artificial Intelligence-Based Poster Layout Design in Visual Communication

Abstract

In visual communication design, the basic design elements include four types of text, graphics, colour, and layout. While the first three can be called visual elements, layout design is the functional arrangement of visual elements. Layout design is as much about making the viewer receive visual information as it is about making them feel attractive. The combination of artificial intelligence and layout design has now become a popular direction in the field of visual communication design. However, the automatic layout design process achieved through an a priori design framework still requires human involvement and is a semi-intelligent application. To solve the above problems, this study proposes a poster layout design method based on artificial intelligence. The layout composition method consists of a learner and a generator. Firstly, the learner uses the spatial transformation network to learn the classification of layout composition elements and form the initial layout design templates for different composition cases. Secondly, the generator optimises the initial template based on the LeNet architecture using the golden ratio and trilateration parameters to produce multiple optimised templates. The templates are then stored in a library of corresponding templates according to their composition and framing style. The experimental results show that the proposed poster layout composition method achieves a higher accuracy rate than existing methods.