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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.
References
- R. Navaneethakrishnan, "Study of Image Compression Techniques," International Journal of Scientific & Engineering Research, Vol. 3, No. 7, pp. 1-5, July 2012.
- G. Boopathy and S. Arockiasam, "Implementation of Vector Quantization for Image Compression - A Survey," Global Journal of Computer Science and Technology, Vol. 10, No. 3, pp. 22-28, April 2010.
- Carlos R. B. Azevedo, Esdras L. Bispo Junior, Tiago A. E. Ferreira, Francisco Madeiro, and Marcelo S. Alencar, "An Evolutionary Approach for Vector Quantization Codebook Optimization," Springer-Verlag Heidelberg, pp. 452-461, 2008.
- Pamela C. Cosman, Karen L. Oehler, Eve A. Riskin, and Robert M. Gray, "Using Vector Quantization for Image Processing," In Proc. Of The IEEE, Vol. 81, No. 9, pp. 1326-1341, September 1993.
- S. Vimala, K. KowsalyaDevi and M. Sathya, " Codebook Generation for Vector Quantization using Interpolations to Compress Gray Scale Images," International Journal of Computer Applications, Vol. 42, No. 9, pp. 14-19, March 2012.
- R. Krishnamoorthi and N. Kannan, "Codebook Generation for Vector Quantization on Orthogonal Polynomials based Transform Coding," International Journal of Information and Communication Engineering, Vol. 5, No. 1, pp. 67-73, 2009.
- Tzu-Chuen Lu and Ching-Yun Chang, "A Survey of VQ Codebook Generation," Journal of Information Hiding and Multimedia Signal Processing, Vol. 1, No. 3, pp. 190-203, July 2010.
- H. B. Kekre and Tanuja K. Sarode, "Vector Quantized Codebook Optimization using K-Means," International Journal on Computer Science and Engineering, Vol. 1, No. 3, pp. 283-290, 2009.
- Y. Linde, A. Buzo, and R. M. Gray, "An algorithm for vector quantizer design," IEEE Trans. Commun. ', Vol. COM-28, No. 1, pp. 84-95, January 1980.
- H. B. Kekre and Tanuja K. Sarode, "Fast Codebook Search Algorithm for Vector Quantization using Sorting Technique," International Conference on Advances in Computing, Communication and Control, pp. 317-325, 2009.
- J. B. MacQueen, "Some Methods for Classification and Analysis of Multivariate Observations", Proceedings of 5th Berkeley symposium on Mathematical Statistics and Probability", Berkely, University of California Press, vol. 1, pp. 281-297, 1967.
- Yujun Lin,Ting Luo, Sheng Yao, Kaikai Mo, Tingting Xu and Caiming Zhong, "An Improved Clustering Method Based on K-means," In Proc. Of 9th International Conference on Fuzzy Systems and Knowledge Discovery, IEEE, pp. 734-737, 2012.
- Bhanu Sukhija and Sukhvir Singh, "Improved K-Means clustering technique using distance determination approach," International Journal of Advanced Research in Computer Science and Electronics Engineering, Vol. 1, No. 5, pp. 31-34, July 2012.
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