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4 March 1996 Color vector quantization by competitive learning
Rusen Meylani, Kemal Ciliz
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Proceedings Volume 2664, Applications of Artificial Neural Networks in Image Processing; (1996) https://doi.org/10.1117/12.234261
Event: Electronic Imaging: Science and Technology, 1996, San Jose, CA, United States
Abstract
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.
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Rusen Meylani and Kemal Ciliz "Color vector quantization by competitive learning", Proc. SPIE 2664, Applications of Artificial Neural Networks in Image Processing, (4 March 1996); https://doi.org/10.1117/12.234261
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KEYWORDS
Quantization
Astatine
Electronics engineering
Neural networks
Printing
RGB color model
Scanners
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