Cheng, Angelina  <br/><br/>
K-means with sampling for determining prominent colors in images 

 - Vol.13(1), Oct 
 - Chennai  ICT Academy  2022 
 - 2813-2819p. 
<br/><br/> A tool that quickly calculates the dominant colors of an image can be<br/>very useful in image processing. The k-means clustering algorithm has<br/>this potential since it partitions a set of data into n clusters and returns<br/>a representative data point from each cluster. We discuss k-means with<br/>sampling for images, which applies k-means clustering to a random<br/>sample of image pixels. We found that even with a small random<br/>sample of pixels from the image, k-means with sampling exhibits no<br/>significant loss of correctness. We examine the usefulness and<br/>limitations of k-means clustering in determining the prominent colors<br/>of an image and identifying trends in large sets of image data. 
<br/><br/><label>Subjects--Topical Terms: </label><br/>Computer Engineering