/COLORTREE

Primary LanguageJupyter Notebook

COLORTREE

[PHOTO SOURCE](https://www.smithsonianmag.com/smart-news/the-scientific-reason-complementary-colors-look-good-together-114030051/)


  1. For every pixels of image, find hue, saturation, value
  2. Scatterplot H(hue), S(saturation), V(value) in cartesian coordinates
  3. Clusterize the scattered points (H, S, V) (Method : K - means, clusternumber = 1 % of datasize)
  4. Scatterplot the centroids in cylindrical coordinates
  5. Add branches, column of the cylindrical colortree

Scatterplot of all HSV points in cartesian coordinates

Scatterplot of all HSV points in cylindrical coordinates

Scatterplot of centroids of HSV derived with K-means cluster analysis(K = 1% of pixel num)