Optimized soft frame design of traditional printing and dyeing process in Xiangxi based on pattern mining and edge-driven scene understanding

Abstract

Traditional folk crafts are handicrafts and corresponding activities created by Chinese working people in all ages to meet their material and spiritual needs by using various material materials and handicrafts. It reflects the general characteristics of arts and crafts, but also shows the distinctive personality of national culture. The folk printing and dyeing process of Miao Nationality in Xiangxi and Southeast Guizhou has this characteristic, which once brought a lot of convenience to people's life and became an important part of people's life at that time. Traditional art carries a lot of spiritual things in its material form, so it has high esthetic value, cultural value and profound spiritual connotation. Therefore, the optimization design of traditional printing and dyeing process framework in Xiangxi is worth studying. In this paper, through using big data pattern mining algorithm and scene understanding algorithm, a framework optimization system of traditional printing and dyeing process in Xiangxi is constructed, for the optimization of the traditional model, the edge-driven scene model is applied for the systematic study. The designed model is simulated through the testing on different data sets. Reflecting from the experimental result, we can conclude that the proposed model is efficient.