@article{(Open Science Index):https://publications.waset.org/pdf/6965,
	  title     = {A Hybrid Approach for Color Image Quantization Using K-means and Firefly Algorithms},
	  author    = {Parisut Jitpakdee and  Pakinee Aimmanee and  Bunyarit Uyyanonvara},
	  country	= {},
	  institution	= {},
	  abstract     = {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.},
	    journal   = {International Journal of Computer and Information Engineering},
	  volume    = {7},
	  number    = {5},
	  year      = {2013},
	  pages     = {600 - 607},
	  ee        = {https://publications.waset.org/pdf/6965},
	  url   	= {https://publications.waset.org/vol/77},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {Open Science Index 77, 2013},