Comparison of three clustering algorithms and an application to color image compression
Jihun Cha, Laurene V. Fausett · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1997
This paper investigates a traditional clustering algorithm (K-means) and two neural networks (SOM and ART-F). The characteristics of each algorithm are illustrated by simulating geometric space data clustering. Then each algorithm is applied to image data sets to compress the size by reducing the number of colors from 256 to 16.