Research on Digital Construction and Design of Minority Clothing Based on Multivariate Statistical Analysis

Abstract

Digitizing minority costumes is a modern way to protect non-heritage. In this paper, after analyzing the Hu invariant moment features and HOG features, we propose a feature extraction method for ethnic minority costumes that integrates the fusion features of HOG features and Hu invariant moment features. On this basis, the structure of the extracted multivariate feature data is analyzed, and the KPCA method of multivariate statistical analysis is adopted to process the multivariate data of ethnic minority costumes and digitally construct and design the ethnic minority costumes. In addition, experiments were conducted to explore the effect of minority costumes on feature extraction and the effect of digitization construction and design. The results show that the extraction accuracy of six ethnic costumes is stable at 0.75, 0.45, 0.50, 0.75, 0.72, and 0.68, respectively, and its Top-10 accuracy reaches 0.61 at the highest level, while the accuracy of retrieving only some of them is less than 0.40, and the effects of constructed ethnic costume outlines are all around 0.9. The output results of ethnic dresses constructed based on this research are roughly similar to the original ethnic dresses, which is conducive to the inheritance of ethnic dress culture.