IMAGE COLOR SEGMENTATION USING K-MEANS CLUSTERING ALGORITHM

Authors

  • Chaitanya Krishna Surryadevara Department of Information Technology

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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Published

2019-11-30

Issue

Section

Articles

How to Cite

Chaitanya Krishna Surryadevara. (2019). IMAGE COLOR SEGMENTATION USING K-MEANS CLUSTERING ALGORITHM. International Journal of Innovations in Engineering Research and Technology, 6(11), 102-110. https://repo.ijiert.org/index.php/ijiert/article/view/3615