Virtual Reality-Based Visual Interaction: A Framework for Classification of Ethnic Clothing Totem Patterns

From the perspective of visual interaction, this paper examines the ethnic characteristics of visual features clothing and the extraction area of the totem ethnic clothing. We employed a feature extraction approach based on extensive data colour and used a classifier to identify the various totems of the ethnic clothing image. We further used PS to extract colour intensities and the DBSCAN algorithm to extract the characteristics of various ethnic colours and examine the phenomenon of judging culture research methods with colour characteristics. With the help of PS, the colour value of multiple images is proposed to provide a scientific and rigorous research method for ethnic minority colour research, improving the efficiency of the DBSCAN clustering algorithm for colour extraction. The obtained results can assist designers to reproduce colour images in their design work. We employed the support vector machine (SVM) to build a classification model to classify and recognize the extracted feature algorithm’s fusion features. The study found that the fusion feature classification and recognition model have higher recognition accuracy. This research lays a good foundation for the information processing of ethnic costumes and contributes to the inheritance and protection of ethnic costume culture.