Intelligent color matching method for smart buildings based on k-means clustering algorithm

Intelligent color matching methods are the future development direction of architectural design due to the extensive use value and development prospect.In this paper, we use web crawler technology to collect data from architectural images in various regions, and perform color recognition as well as data processing on the images based on Reinex theory.Adaptive K-means++ clustering method and intelligent color matching method are proposed.The study firstly screens 450 collected images of different types of buildings.The color characteristics of country house, gothic building, a European house and garden building images were used to do the grayscale histogram color evaluation, and the analysis was mainly carried out with country house, gothic building, a European house and garden building image types, in which the color range of country house building types is small, the color is dark, and there is little difference in the color of the images.Then selected Jiangsu, Zhejiang, Hangzhou three regions of the building image color as a practical case, the use of K-means + + clustering method of the three regions of the building color characteristics of the clustering, the calculation of the building color ratio, color dispersion indicators and constructed a color network model, based on the results of the calculation of the three regions of the color of the judgment of the similarity of the color, based on the similarity of the color of the completion of the building color intelligent Matching.The experimental results show that the building color similarity between Jiangsu region and Henan region is high, which verifies that the color intelligent matching method proposed in this paper has high efficiency and high matching accuracy.