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K-Means Codebook Optimization using KFCG Clustering Technique
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 78 - Number 6 |
| Year of Publication: 2013 |
| Authors: Tanuja K. Sarode, Nabanita Mandal |
10.5120/13496-1228
|
Tanuja K. Sarode, Nabanita Mandal . K-Means Codebook Optimization using KFCG Clustering Technique. International Journal of Computer Applications. 78, 6 ( September 2013), 38-43. DOI=10.5120/13496-1228
Abstract
Codebook Optimization is a concept of vector quantization which is applied to achieve lossy compression. Optimization of the codebook helps in maintaining the quality of the image. The codebook is generated using Kekre's Fast Codebook Generation (KFCG) algorithm and Random Selection Method. The K-means algorithm is used to optimize the codebook. The Mean Square Error (MSE) is used as the measurement parameter. The point where the MSE converges is the optimal point and the codebook at that point is said to be the optimized codebook. The results obtained show that when K-means algorithm is applied to the codebook generated by KFCG Algorithm, less MSE is obtained as compared to Random Selection Method.
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