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K Means Algorithm with the application to image compression

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K Means Algorithm with the application to image compression

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This program uses the K means clustering algorithm to group the pixels in an image

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Description

- K means algorithm is performed with different initial centroids in order to get the best clustering.
- The total cost is calculated by summing the distance of each point to its cluster centre and then summing over all the clusters.
- Based on the minimum overall cost achieved during each iteration of 'iterKMeans' the pixel assignment to their respective clusters are made and final compressed image is obtained.
- This algorithm will run slower as the number of clusters , size of the image and number of iterations increase.

MATLAB release MATLAB 7.14 (R2012a)
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Comments and Ratings (2)
14 Oct 2013 Gabriel  
25 Jul 2013 Jason Rebello

hey guys, let me know what you think of the code, if there is anything you like about it or improvements that can be made to it. Thanks

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