K-Means Clustering in OpenCV and Application for Color Quantization
The k-means clustering algorithm is an unsupervised machine learning technique that seeks to group similar data into distinct clusters to uncover patterns in the data that may not be apparent to the naked eye.
It is possibly the most widely known algorithm for data clustering and is implemented in the OpenCV library.
In this tutorial, you will learn how to apply OpenCV’s k-means clustering algorithm for color quantization of images.
After completing this tutorial, you will know:
- What data clustering is within the context of machine learning.
- Applying the k-means clustering algorithm in OpenCV to a simple two-dimensional dataset containing distinct data clusters.
- How to apply the k-means clustering algorithm in OpenCV for