WASET
	%0 Journal Article
	%A Parisut Jitpakdee and  Pakinee Aimmanee and  Bunyarit Uyyanonvara
	%D 2013
	%J International Journal of Computer and Information Engineering
	%B World Academy of Science, Engineering and Technology
	%I Open Science Index 77, 2013
	%T A Hybrid Approach for Color Image Quantization Using K-means and Firefly Algorithms
	%U https://publications.waset.org/pdf/6965
	%V 77
	%X Color Image quantization (CQ) is an important
problem in computer graphics, image and processing. The aim of
quantization is to reduce colors in an image with minimum distortion.
Clustering is a widely used technique for color quantization; all
colors in an image are grouped to small clusters. In this paper, we
proposed a new hybrid approach for color quantization using firefly
algorithm (FA) and K-means algorithm. Firefly algorithm is a swarmbased
algorithm that can be used for solving optimization problems.
The proposed method can overcome the drawbacks of both
algorithms such as the local optima converge problem in K-means
and the early converge of firefly algorithm. Experiments on three
commonly used images and the comparison results shows that the
proposed algorithm surpasses both the base-line technique k-means
clustering and original firefly algorithm.
	%P 600 - 607