KMeans and Vector Quantization

KMeans clustering is a type of Vector Quantization ("Since vector quantization is a natural application for k-means, information theory terminology is often used."[1] ).

From Machine Learning perspective, feature vectors can be considered as code-word and the table mapping code-word to cluster ids is a codebook.

Each feature vector to be clustered is considered as a code-word and in KMeans clustering, they are assigned to the closest centroid (cluster id).

Pages describing Vector Quantization - KMeans:

1. Vector Quantization
2. Documentation on K-means clustering and VQ in Python
3. KMeans in OpenCV using C++.