Research on the Application of Artistic Elements in Plastic Packaging Design Based on the Vision of Multivariate Statistical Analysis Inheritance

Abstract

Abstract Characteristics with humanization and cultural heritage have become a new trend in plastic packaging design, and the integration of traditional art elements can effectively help complete the design. In this paper, the image of traditional culture and art is segmented and processed, and the description of regional significant values is realized through the multivariate statistics of regional features, and the constituent elements of art images are analyzed from different features. After extracting elements statistically, the traditional style migration of art elements is completed using a VGG network. To address the issue of slow optimization calculations during the iterative process, an offline model is used to achieve fast migration. In practice, the dynamic set ArtEleData is constructed based on the art and culture images of some ethnic minorities, and the evolution of the main elements such as clothing, food, shelter, and passages is studied, and the effect of the plastic packaging design using the above elements as the migrating body is measured. The color composition of the migrated art elements is the same as that of the plastic packaging design generated in this paper, with a small difference in the color ratio, and the average difference of different colors is 0.541. Among them, “12G” has the highest similarity in color moment characteristics, with a color moment of 0.00569, which proves the effectiveness of the migrated design of the art element packaging. This proves the effectiveness of the packaging migration design for artistic elements.