/ImageSegmentationUsing_KMeans

Image segmentation using opencv

Primary LanguagePython

ImageSegmentationUsing_KMeans

  • To reduce the number of color points in an image using supervised learning. This application is also referred to as image segmentation or color quantization
  • K-means algorithm is used for image segmentaion

Team Members

  • Ankita Patil
  • Abhilash Gudasi

Tools, libraries used

  • Language used: Python
  • Libraries used: opencv, numpy

Input

Image segmentation algorithm is run on 3 images which can be found here

Parameters

It is upto you to select the best value of the number of clusters and any other parameters for the algorithm

Compile and Run Instructions:

Commands to run:

  ImageSegmentationUsingKMeans.py <Path to Image1> <Path to Image2> <Path to Image3>

Example command

  python ImageSegmentationUsingKMeans.py image1.jpg image2.jpg image3.jpg

Output

Output is a set of clustered images and stored in a folder named clusteredImages which can be found here

References