Image generation by using k-means clustering technique
Keywords:
K-means Algorithm, Clustering, colorizationAbstract
This paper presents a new approach for image generation by applying k-means algorithm. The K-means clustering algorithm is one of the most widely used algorithm in the literature, and many authors successfully compare their new proposal with the results achieved by the k-Means. Our research proposes a color-based image generation method that uses K-means clustering technique which is an iterative technique used to partition an image into k clusters. At first the pixels of source image are clustered into k partitions based on their color, where the clustering process is accomplished. Then the clustered colors are merged to generate the target image. After applying K-means algorithm for different values of k (no. of colors), Mean Square Error (MSE) and processing time are evaluated for different types of image. This approach thus provides a feasible new solution for image generation which may be helpful in image compression.
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