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Proceedings Paper

In search of a new initialization of K-means clustering for color quantization
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Paper Abstract

Color quantization is still an important auxiliary operation in the processing of color images. The K-means clustering (KM), used to quantize the color, requires an appropriate initialization. In this paper, we propose a combined KM method that use to initialize the results of well-known quantization algorithms such as Wu's, NeuQuant (NQ) and Neural Gas (NG). This approach, assessed by three quality indices: PSNR, ΔE and ΔM, improves the results. Experimental results of such combined quantization indicate that the deterministic Wu+KM and random NG+KM approaches leading to the best quantized images.

Paper Details

Date Published: 8 December 2015
PDF: 5 pages
Proc. SPIE 9875, Eighth International Conference on Machine Vision (ICMV 2015), 987506 (8 December 2015); doi: 10.1117/12.2228712
Show Author Affiliations
Mariusz Frackiewicz, Silesian Univ. of Technology (Poland)
Henryk Palus, Silesian Univ. of Technology (Poland)

Published in SPIE Proceedings Vol. 9875:
Eighth International Conference on Machine Vision (ICMV 2015)
Antanas Verikas; Petia Radeva; Dmitry Nikolaev, Editor(s)

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