In this paper, color vector quantization is performed by a competitive learning based clustering algorithm with some modifications that eliminate the false colors that may appear on the resulting image. The preliminary operations that must be applied to the input image pixels before the algorithm can be applied are also stated. Moreover, it is demonstrated that with this scheme, faster convergence and less computations are possible using only a small fraction of all the pixels, but at the same time producing satisfactory results. Finally the results are compared to those of the K-means clustering algorithm.

Date Published: 4 March 1996
PDF: 4 pages
Proc. SPIE 2664, Applications of Artificial Neural Networks in Image Processing, (4 March 1996); doi: 10.1117/12.234261

Published in SPIE Proceedings Vol. 2664:
Applications of Artificial Neural Networks in Image Processing
Nasser M. Nasrabadi; Aggelos K. Katsaggelos, Editor(s)