@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}, }