We apologize for a recent technical issue with our email system, which temporarily affected account activations. Accounts have now been activated. Authors may proceed with paper submissions. PhDFocusTM
CFP last date
20 December 2024
Reseach Article

‘RGB’ Color Image Quantization using Pollination based Optimization

by Gaganpreet Kaur, Dheerendra Singh, Gurjeet Kaur
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 78 - Number 9
Year of Publication: 2013
Authors: Gaganpreet Kaur, Dheerendra Singh, Gurjeet Kaur
10.5120/13517-1297

Gaganpreet Kaur, Dheerendra Singh, Gurjeet Kaur . ‘RGB’ Color Image Quantization using Pollination based Optimization. International Journal of Computer Applications. 78, 9 ( September 2013), 18-22. DOI=10.5120/13517-1297

@article{ 10.5120/13517-1297,
author = { Gaganpreet Kaur, Dheerendra Singh, Gurjeet Kaur },
title = { ‘RGB’ Color Image Quantization using Pollination based Optimization },
journal = { International Journal of Computer Applications },
issue_date = { September 2013 },
volume = { 78 },
number = { 9 },
month = { September },
year = { 2013 },
issn = { 0975-8887 },
pages = { 18-22 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume78/number9/13517-1297/ },
doi = { 10.5120/13517-1297 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:51:08.595499+05:30
%A Gaganpreet Kaur
%A Dheerendra Singh
%A Gurjeet Kaur
%T ‘RGB’ Color Image Quantization using Pollination based Optimization
%J International Journal of Computer Applications
%@ 0975-8887
%V 78
%N 9
%P 18-22
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Color Image Quantization plays an important role for image analysis and visualization. In this paper, RGB color image quantization using pollination based optimization is implemented. The pollination based optimization is applied to RGB color model for image quantization. The Euclidean Distance metric is used for color difference between pixels. Color elimination and reproduction is done by evaluating the Euclidean Distance. Threshold value is taken as the fitness function to calculate the popular and unpopular colors. Color difference calculated using Euclidean Distance and correlate better with visual assessment than color differences calculated using other distance metrics. In order to evaluate the performance of proposed algorithm, MSE (Mean Square Error), Euclidean Distance, Correlation coefficient, PSNR, Time Taken (in seconds) is used. Experimental results shows that MSE values are significantly reduced and we achieve better PSNR and Correlation coefficient values.

References
  1. P. Heckbert, "Color Image Quantization for Frame Buffer Display", ACM Computer Graphics, Vol. 16, No. 3, pp. 297–307, 1982.
  2. Scheunders P,"A genetic C-means clustering algorithm applied to color image quantization", Pattern Recognition30 (6), pp. 859-866, 1997.
  3. Xiang Z, Joy G, "Color image quantization by agglomerative clustering", IEEE Computer Graphics and Applications 14(3), pp. 44-48, 1994.
  4. Thakar, J. D, Kunte,K, Chauhan,A. K , Watve,A. V, Watve,M. G. , "Nectarless flowers: ecological correlates and evolutionary stability", Oecologia. 136, pp. 565-570, 2003.
  5. Prajakta V. , et al. , "The co-optimization of floral display and nectar reward", Journal of Biosciences, Vol No. 34(6), pp 1-5, 2009.
  6. Kumar, S. , Singh, A. , "Pollination based optimization," Presented at 6th International Multi Conference on Intelligent Systems, Sustainable, New and Renewable Energy Technology and Nanotechnology IISN2012, pp. 269-273, 2012.
  7. Velho, L. , Gomes J. , Sobrerio, M. , "Color image quantization using pairwise clustering", Proceedings of the 10th Brazilian Symposium on Computer Graphics and Image Processing, pp. 203-207.
  8. Kaur, G and Singh, D. "Pollination Based Optimization For Color Image Segmentation", International Journal Of Computer Engineering & Technology, pp. 407-414, Volume 3, Issue 2, July- September, 2012.
  9. Rui X, Chang C, Srikanthan T. , "On the initialization and training methods for Kohonen self-organising feature maps in color image quantization", ,Proceedings of the 1st IEEE International Workshop On Electronic Design ,Test and Applications,2002.
  10. Dekker A. , "Kohonen neural networks for optimal color quantization", Network: Computation in Neural Systems 5, pp. 351-367, 1994.
  11. Kaur, Rajinder et al. , "Color Image Quantization based on Bacteria Foraging Optimization ", International Journal of Computer Applications, pp. 975 – 979, Volume 25, Issue 7, July 2011.
  12. Orchard, M. and Bouman, C. , "Color Quantization of Images," IEEE Trans. on Sig. Proc. , pp. 2677-2690. Volume 39, Issue 12, Dec. 1997.
  13. Sadegi, Z. , Teshnehlab, M. and Pedram, M. , "K-Ants Clustering – A New Strategy Based On Ant Clustering," proceedings of 2nd York doctoral symposium on computing ,university of York, UK,2008.
  14. Velho, L. "Color Image Quantization by Pairwise Clustering", IMPA–Instituto de Matematica Pura e Aplicada, Estrada Dona Castorina, 2010.
  15. Wang, Z. , Wu, G. , Yang. E and Bovik, A. C. , "Quality-aware images," IEEE Transactions on Image Processing, vol. 15, pp. 1680-1689, 2006.
  16. Omran, M. G. ,Engelbrecht A. P. and Salman ,A. "A Color Image Quantization Algorithm Based on Particle Swarm Optimization," Informatica 29(2005)261-269.
  17. Pujol, A. and Liming, Chen. , "Color Quantization for image processing using self information", 6th IEEE International Conference on Information, Communication and signal processing, 2007.
  18. Bansal, S. Aggarwal, D. , "Color Image Segmentation using CIELab Color Space using Ant Colony Optimization", International Journal of Computer Applications, pp. 28-34, 2011.
  19. Chang, Y. , Liang, D. "A Robust Color Image Quantization Algorithm Based on Knowledge Reuse of K-Means Clustering Ensemble", Journal of Multimedia, 2000.
  20. Heena and Aggarwal, H. , "Color Image Quantization Based on Euclidean Distance Using Bacteria Foraging Optimization," International Journal of Electronics and Computer Science Engineering, ISSN 2277-1956/V1N4-2285-2290
  21. Jiang, Y. , Wang, Y. and Jin, L. , "Investigation on Color Quantization Algorithm of Color Image," ECWAC 2011, Part II, CCIS 144, pp. 181–187, Springer-Verlag Berlin Heidelberg 2011.
  22. Jain, A. k, Murty, M. N and Flynn, P. J "Data Clustering: A Review", ACM Computing Surveys, Vol. 31 (3), pp. 264-323, 1999.
  23. Jaffer, Mohammad, A. , O. , and R. Shiva Kumar, "Ant Based Clustering Algorithm: A brief Survey", International Journal of computer Theory and Engineering, Volume 2, No. 5, pp. 1793-8201.
  24. Jang et. al, "Neuro-Fuzzy and Soft Computing, A Computational Approach to Learning and Machine Intelligence", Prentice Hall of India, 2004.
  25. Kumar, D. and Chopra, V. , "Image Quantization Using HSI Based On Bacteria Foraging Optimization", International Journal of Information Technology and Knowledge Management, pp. 335-343, Volume 5, Issue. 2, 2012.
  26. Xin, L. and Xaisoqi, L. , "Multiple Digital Watermarking Algorithm to protect Digital images based on integer wavelet matrix norm quantization", pp 569-571, IEEE, 2009.
  27. Yarde, P. and Gupta, N. , "Survey of Color Image Quantization Algorithms Based on Swarm Intelligence" International Journal of Systems, Algorithms & Applications, Volume 2, Issue ICASE 2012, August 2012, ISSN Online: 2277-2677.
  28. Zhang, M. and Bermak, A. , "Architecture of a Digital Pixel Sensor Array with Tile-based Vector Quantization Image Compression Algorithm", Digital Image Computing Techniques and Applications, 9th Biennial Conference of the Australian Pattern Recognition Society, IEEE, pp. 541-546, 2007.
Index Terms

Computer Science
Information Sciences

Keywords

Quantization Segmentation Optimization Pollination Based Optimization Euclidean Distance RGB color Space