Comparison of three clustering algorithms and an application to color image compression

Jihun Cha; Laurene V. Fausett

doi:10.1117/12.271482

4 April 1997 Comparison of three clustering algorithms and an application to color image compression

Jihun Cha, Laurene V. Fausett

Proceedings Volume 3077, Applications and Science of Artificial Neural Networks III; (1997) https://doi.org/10.1117/12.271482
Event: AeroSense '97, 1997, Orlando, FL, United States

Abstract

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.

Citation Download Citation

Jihun Cha and Laurene V. Fausett "Comparison of three clustering algorithms and an application to color image compression", Proc. SPIE 3077, Applications and Science of Artificial Neural Networks III, (4 April 1997); https://doi.org/10.1117/12.271482

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