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Implementation & Learning of Compression of Image through use of K-means Clustering Algorithm

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Vatshayan/Machine-Learning-Project-for-Image-Compression

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Image-Compression-Using-Machine-Learning

KMeans Clustering algorithm is used for Image Compression.

Image compression is compressing Image to lower quality from Original Quality. So, that less space should be ocupied in database. So, By this We can say Many stuff can be deal through Machine learning Algorithms.

The web is loaded up with enormous measures of information as pictures. Individuals transfer a great many pictures each day via online media locales, for example, Instagram, Facebook and distributed storage stages, for example, google drive, and so on. With such a lot of information, image compression techniques become important to compress the images and reduce storage space.

In this Project, we will take a look at image compression using K-means clustering algorithm which is an unsupervised learning algorithm.

An image is made up of several intensity values known as Pixels. In a colored image, each pixel is of 3 bytes containing RGB (Red-Blue-Green) values having Red intensity value, then Blue and then Green intensity value for each pixel.


Contact me ([email protected]) for project PPT, Synopsis, Code and Research papers on this topic.

I have a new Updated Python Code too. If anyone wants then mail me ([email protected]).

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