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A Hybrid Approach for Color Image Quantization Using K-means and Firefly Algorithms

Authors: Parisut Jitpakdee, Pakinee Aimmanee, Bunyarit Uyyanonvara


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.

Keywords: Clustering, Color quantization, Firefly algorithm, Kmeans.

Digital Object Identifier (DOI):

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