As an urban cultural communication carrier, metro space is characterized by dense flow of people and closed space, which is an excellent medium for displaying regional culture. Computer-aided technology provides a scientific method for the extraction and translation of regional cultural elements, which makes the subway space design more local characteristics. In this study, K-Means clustering algorithm and LBP (Local Binary Pattern) algorithm are used to extract the color and texture features of the Shaanxi folk art element-horse spoon, construct a color network model to analyze the color matching law, and convert the cultural elements into design elements through the regional culture translation model, which is applied to the spatial design of Xi’an Metro Line 4. The results show that the K-Means algorithm has high accuracy in color extraction; the LBP algorithm outperforms the five algorithms of GLCM, EOG, SGS, CS and SOP in four texture dataset tests, and at the same time has the shortest feature extraction time. The practical design effect survey shows that 72%~76% of the 500 passengers are satisfied with the spatial design of Xi’an Metro Line 4 that incorporates regional culture. This study provides new ideas for the scientific extraction and artistic translation of regional culture in urban public space, effectively solves the problem of “a thousand stations in one place” in metro space, and realizes the harmonious unity of regional culture and modern design.
