TY  - GEN
AU  - Cheng, Angelina 
AU  - Rosenberg, Eric 
TI  - K-means with sampling for determining prominent colors in images
PY  - 2022///
CY  - Chennai
PB  - ICT Academy
KW  - Computer Engineering
N2  - A tool that quickly calculates the dominant colors of an image can be
very useful in image processing. The k-means clustering algorithm has
this potential since it partitions a set of data into n clusters and returns
a representative data point from each cluster. We discuss k-means with
sampling for images, which applies k-means clustering to a random
sample of image pixels. We found that even with a small random
sample of pixels from the image, k-means with sampling exhibits no
significant loss of correctness. We examine the usefulness and
limitations of k-means clustering in determining the prominent colors
of an image and identifying trends in large sets of image data
UR  - https://ictactjournals.in/paper/IJSC_Vol_13_Iss_1_Paper_10_2813_2819.pdf
ER  -