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 # Color-Ouantization
-Coloring an image with 'K' Colors using K-Means Coloring
+Coloring an image with 'K' Colors using K-Means Coloring. Here we implement K-Means Clustering by using only basic Numpy operations and opencv.imread() to perform Color Quantization on an Image. 
 
-Here we implement K-Means Clustering by using only basic Numpy operations and opencv.imread() to perform Color Quantization on an Image.
+## Color Quantization Definition :
+  It refers to reducing the number of colors used to represent an image. We color the image in 'k' number of colors by using K-Means Clustering. 
+
+## Flow of Code :
+1.  Take an input image with the desired number of colors (k) and add the threshold of when to stop updating.
+2.  Randomly initialize the centers of the Clusters. 
+3.  Calculating distance of each point w.r.t each Centroid and Classifing the Points to the corresponding Centroid.
+4.  Store all points in terms of the Centroid to which they are assigned.
+5.  Recompute the Mean of each Centroid
+6.  Paint the image with the Mu value of each Cluster to the corresponding pixel value.