IMAGE COLOR SEGMENTATION USING K-MEANS CLUSTERING ALGORITHM
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Abstract
Working with images can be a very time-consuming task, especially if you have many images to work on. Machine learning can thus be a great time-saver for various image analysis and editing tasks, such as finding the dominant colors of an image thanks to the K-means clustering algorithm. The K-means clustering algorithm defines a number K of clusters and the best “centroids” to cluster the data around. When applied to images, it allows extracting the k dominant colors in an image to be used for other purposes.
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