Explore the fascinating connections between color changes and global art movements in the "Making Art Sm‘art’er" article. Delve into the challenges and innovative solutions used in grouping paintings based on color trends, frontend frameworks like D3 + Svelte, and the utilization of pixel clustering
Explore the fascinating world of color extraction and computer vision in our latest article. Discover how k-means clustering, an unsupervised machine learning algorithm, is used to extract dominant colors from paintings. Learn about raster and vector graphics, RGB color spaces, and the comparison between K-means
This article explores the use of clustering algorithms and art museum APIs to extract dominant color palettes from artworks, with a focus on the collection of the Art Institute of Chicago. The authors demonstrate how to programmatically access image and metadata, extract color statistics, and
Team Splatoon introduced the Georgia Tech Spring 2023 Practicum Project where we partner with Budget Collector to determine relationships between colors and their regions, time periods, or other data of interest. We experimented with color quantization methods via k-means and median cut. We found that