CFP last date
20 January 2025
Call for Paper
February Edition
IJCA solicits high quality original research papers for the upcoming February edition of the journal. The last date of research paper submission is 20 January 2025

Submit your paper
Know more
The week's pick
Responsive image
HYBRID ANN AND FIREWORKS ALGORITHM FOR REAL-TIME SOFTWARE RELIABILITY PREDICTION

Ivy Botchway Felix Larbi Aryeh Boniface Kayode Alese
Random Articles
Reseach Article

Performance Comparison of LBG, KPE, KFCG and KMCG for Global Codebook Technique

by Dr. H. B. Kekre, Dr.Tanuja K. Sarode, Kavita Raut, Rohan Tahiliani
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 30 - Number 10
Year of Publication: 2011
Authors: Dr. H. B. Kekre, Dr.Tanuja K. Sarode, Kavita Raut, Rohan Tahiliani
10.5120/3680-5025

Dr. H. B. Kekre, Dr.Tanuja K. Sarode, Kavita Raut, Rohan Tahiliani . Performance Comparison of LBG, KPE, KFCG and KMCG for Global Codebook Technique. International Journal of Computer Applications. 30, 10 ( September 2011), 42-50. DOI=10.5120/3680-5025

@article{ 10.5120/3680-5025,
author = { Dr. H. B. Kekre, Dr.Tanuja K. Sarode, Kavita Raut, Rohan Tahiliani },
title = { Performance Comparison of LBG, KPE, KFCG and KMCG for Global Codebook Technique },
journal = { International Journal of Computer Applications },
issue_date = { September 2011 },
volume = { 30 },
number = { 10 },
month = { September },
year = { 2011 },
issn = { 0975-8887 },
pages = { 42-50 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume30/number10/3680-5025/ },
doi = { 10.5120/3680-5025 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:16:40.961095+05:30
%A Dr. H. B. Kekre
%A Dr.Tanuja K. Sarode
%A Kavita Raut
%A Rohan Tahiliani
%T Performance Comparison of LBG, KPE, KFCG and KMCG for Global Codebook Technique
%J International Journal of Computer Applications
%@ 0975-8887
%V 30
%N 10
%P 42-50
%D 2011
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Vector quantization is a classical quantization technique from signal processing which allows the modeling of probability density functions by the distribution of prototype vectors. It was originally used for data compression. It works by dividing a large set of points (vectors) into groups having approximately the same number of points closest to them. Each group is represented by its centroid point, as in clustering algorithms. Vector Quantization is a technique of compressing data based on grouping blocks having similar data. These blocks are called Code Vectors and all the code vectors grouped together is called a Codebook. The key to VQ data compression is a good codebook. In order to reduce bandwidth overhead it is necessary to generate Global Codebook for a particular class of images. Otherwise local codebook has to be transferred every time before the transmission of image. In this paper various global codebook generation algorithms for vector quantization for color images are presented.

References
  1. Jeng-Shyang Pan, Zhe-Ming Lu, and Sheng-He Sun.: ‘An Efficient Encoding Algorithm for Vector Quantization Based on Subvector Technique’, IEEE Transactions on image processing, vol 12 No. 3 March 2003.
  2. R. M. Gray.: ‘Vector quantization’, IEEE ASSP Mag., pp. 4-29, Apr.1984.
  3. 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, 1980.
  4. Gersho, R.M. Gray.: ‘Vector Quantization and Signal Compressio’, Kluwer Academic Publishers, Boston, MA, 1991.
  5. Chin-Chen Chang, Wen-Chuan Wu, “Fast Planar-Oriented Ripple Search Algorithm for Hyperspace VQ Codebook”, IEEE Transaction on image processing, vol 16, no. 6, June 2007.
  6. Momotaz Begum, Nurun Nahar, Kaneez Fatimah, M. K. Hasan, and M. A. Rahaman: ‘An Efficient Algorithm for Codebook Design in Transform Vector Quantization’, WSCG’2003, February 3-7, 2003.
  7. Robert Li and Jung Kim: ‘Image Compression Using Fast Transformed Vector Quantization’, 29th Applied Imagery Pattern Recognition Workshop, 2000, pp. 141 – 145, Apr. 2000.
  8. Zhibin Pan; Kotani, K.; Ohmi, T., ‘Enhanced fast encoding method for vector quantization by finding an optimally-ordered Walsh transform kernel’, ICIP 2005, IEEE International Conference, Volume 1, Issue, 11-14, Page(s): I - 573-6, Sept. 2005.
  9. Jim Z.C. Lai, Yi-Ching Liaw, and Julie Liu, “A fast VQ codebook generation algorithm using codeword displacement”, Pattern Recogn. vol. 41, no. 1, pp 315–319, 2008.
  10. Y.C. Liaw, J.Z.C. Lai, W. Lo, Image restoration of compressed image using classified vector quantization, Pattern Recogn. vol. 35, No. 2, pp 181–192, 2002.
  11. N.M. Nasrabadi, Y. Feng, Image compression using address vector quantization, IEEE Trans. Commun. vol. 38 No. 12, pp. 2166–2173, 1990.
  12. J. Foster, R.M. Gray, M.O. Dunham, Finite state vector quantization for waveform coding, IEEE Trans. Inf. Theory vol. 31, No. 3, pp. 348–359, 1985.
  13. T. Kim, Side match and overlap match vector quantizers for images, IEEE Trans. Image Process. vol. 1, No. 2, pp. 170–185, 1992.
  14. J. Z. C. Lai, Y.C. Liaw, W. Lo, Artifact reduction of JPEG coded images using mean-removed classified vector quantization, Signal Process. vol. 82, No. 10, pp. 1375–1388, 2002.
  15. K. N. Ngan, H.C. Koh, Predictive classified vector quantization, IEEE Trans. Image Process. vol. 1, No. 3, pp. 269–280, 1992
  16. S. C. Lo, H. P. Chan, J. S. Lin, H. Li, M. T. Freedman, and S. K. Mun, “Artificial convolution neural network for medical image pattern recognition,” Neural Networks, vol.8, no. 7/8, pp. 1201–1214, 1995.
  17. 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, 1980
  18. H.B.Kekre, Tanuja K. Sarode, “New Fast Improved Clustering Algorithm for Codebook Generation for Vector Quantization”, International Conference on Engineering Technologies and Applications in Engineering, Technology and Sciences, Computer Science Department, Saurashtra University, Rajkot, Gujarat. (India), Amoghsiddhi Education Society, Sangli, Maharashtra (India) , 13th – 14th January 2008.
  19. H. B. Kekre, Tanuja K. Sarode, “New Fast Improved Codebook Generation Algorithm for Color Images using Vector Quantization,” International Journal of Engineering and Technology, vol.1, No.1, pp.: 67-77, September 2008.
  20. H. B. Kekre, Tanuja K. Sarode, “Fast Codebook Generation Algorithm for Color Images using Vector Quantization,” International Journal of Computer Science and Information Technology, Vol. 1, No. 1, pp.: 7-12, Jan 2009.
  21. H. B. Kekre, Tanuja K. Sarode, “An Efficient Fast Algorithm to Generate Codebook for Vector Quantization,” First International Conference on Emerging Trends in Engineering and Technology, ICETET-2008, held at Raisoni College of Engineering, Nagpur, India, pp.: 62- 67, 16-18 July 2008. Avaliable at IEEE Xplore.
  22. H. B. Kekre, Tanuja K. Sarode, “Fast Codebook Generation Algorithm for Color Images using Vector Quantization,” International Journal of Computer Science and Information Technology, Vol. 1, No. 1, pp.: 7-12, Jan 2009.
  23. H. B. Kekre, Tanuja K. Sarode, “Fast Codevector Search Algorithm for 3-D Vector Quantized Codebook”, WASET International Journal of cal Computer Information Science and Engineering (IJCISE), Volume 2, No. 4, pp.: 235-239, Fall 2008. Available: http://www.waset.org/ijcise.
  24. H. B. Kekre, Tanuja K. Sarode, “Fast Codebook Search Algorithm for Vector Quantization using Sorting Technique”, ACM International Conference on Advances in Computing, Communication and Control (ICAC3-2009), pp: 317-325, 23-24 Jan 2009, Fr. Conceicao Rodrigous College of Engg., Mumbai. Available on ACM portal.
  25. Jim Z.C. Lai, Yi-Ching Liaw, and Julie Liu, “A fast VQ codebook generation algorithm using codeword displacement”, Pattern Recogn. vol. 41, no. 1, pp.: 315–319,2008.
  26. C.H. Hsieh, J.C. Tsai, Lossless compression of VQ index with search order coding, IEEE Trans. Image Process. vol. 5, No. 11, pp.: 1579–1582, 1996.
  27. Chin-Chen Chang, Wen-Chuan Wu, “Fast Planar-Oriented Ripple Search Algorithm for Hyperspace VQ Codebook”, IEEE Transaction on image processing, vol 16, no. 6, pp.: 1538-1547, June 2007.
  28. Garcia and G. Tziritas, “Face detection using quantized skin color regions merging and wavelet packet analysis,”= IEEE Trans. Multimedia, vol. 1, no. 3, pp.: 264–277, Sep. 1999.
  29. H. Y. M. Liao, D. Y. Chen, C. W. Su, and H. R. Tyan, “Real-time event detection and its applications to surveillance systems,” in Proc. IEEE Int. Symp. Circuits and Systems, Kos, Greece, pp.: 509–512, May 2006.
  30. J. Zheng and M. Hu, “An anomaly intrusion detection system based on vector quantization,” IEICE Trans. Inf. Syst., vol. E89-D, no. 1, pp.: 201–210, Jan. 2006.
  31. H. B. Kekre, Tanuja K. Sarode, Bhakti Raul, ”Color Image Segmentation using Kekre’s Fast Codebook Generation Algorithm Based on Energy Ordering Concept”, ACM International Conference on Advances in Computing,Communication and Control (ICAC3-2009), pp.: 357-362, 23-24 Jan 2009, Fr. Conceicao Rodrigous College of Engg., Mumbai. Available on ACM portal.
  32. H. B. Kekre, Tanuja K. Sarode, Bhakti Raul, “Color Image Segmentation using Kekre’s Algorithm for Vector Quantization”, International Journal of Computer Science(IJCS), Vol. 3, No. 4, pp.: 287-292,Fall2008. Available:http://www.waset.org/ijcs.
  33. H. B. Kekre, Tanuja K. Sarode, Bhakti Raul, “Color Image Segmentation using Vector Quantization Techniques Based on Energy Ordering Concept” International Journal of Computing Science and Communication Technologies (IJCSCT) Volume 1, Issue 2, pp: 164-171, January 2009.
  34. H. B. Kekre, Tanuja K. Sarode, Bhakti Raul, “Color Image Segmentation Using Vector Quantization Techniques”,Advances in Engineering Science Sect. C (3), pp.: 35-42,July-September 2008.
  35. H. B. Kekre, Tanuja K. Sarode, “Speech Data Compression using Vector Quantization”, WASET International Journal of Computer and Information Science and Engineering (IJCISE), vol. 2, No. 4, pp.: 251-254, Fall 2008.
  36. H. B. Kekre, Ms. Tanuja K. Sarode, Sudeep D. Thepade,“Image Retrieval using Color-Texture Features from DCT on VQ Codevectors obtained by Kekre’s Fast Codebook Generation”, ICGST-International Journal on Graphics, Vision and Image Processing (GVIP), Volume 9, Issue 5, pp.: 1-8, September 2009.
  37. H. B. Kekre, Kamal Shah, Tanuja K. Sarode, Sudeep D. Thepade,”Performance Comparison of Vector Quantization Technique – KFCG with LBG, Existing Transforms and PCA for Face Recognition”, International Journal of Information Retrieval (IJIR), Vol. 02, Issue 1, pp.: 64-71, 2009.
Index Terms

Computer Science
Information Sciences

Keywords

Vector Quantization Clustering Global Codebook

Powered by PhDFocusTM