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Image Compression Using Clustering Algorithms - K-means & K-medoids

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Image Compression

  • Given a RGB bitmap image file, clustered the pixels using clustering algorithms
  • Created the final compressed image by coloring each cluster with the representative color of it’s centroid.

Clustering Algoithms Used

  • K-means
  • K-medoids

K-Medoids

  • Manhattan Distance Used as Distance Metric
  • Partitioning Around Medoids (PAM) Algorithm

How to run

  • run mainprogram(filename, no of clusters)
  • Eg: run mainprogram(‘beach.bmp’, 3)

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Image Compression Using Clustering Algorithms - K-means & K-medoids

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