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Reseach Article

Image Classification using Block Truncation Coding with Assorted Color Spaces

by H. B. Kekre, Sudeep Thepade, Rik Kamal Kumar Das, Saurav Ghosh
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 44 - Number 6
Year of Publication: 2012
Authors: H. B. Kekre, Sudeep Thepade, Rik Kamal Kumar Das, Saurav Ghosh
10.5120/6265-8418

H. B. Kekre, Sudeep Thepade, Rik Kamal Kumar Das, Saurav Ghosh . Image Classification using Block Truncation Coding with Assorted Color Spaces. International Journal of Computer Applications. 44, 6 ( April 2012), 9-14. DOI=10.5120/6265-8418

@article{ 10.5120/6265-8418,
author = { H. B. Kekre, Sudeep Thepade, Rik Kamal Kumar Das, Saurav Ghosh },
title = { Image Classification using Block Truncation Coding with Assorted Color Spaces },
journal = { International Journal of Computer Applications },
issue_date = { April 2012 },
volume = { 44 },
number = { 6 },
month = { April },
year = { 2012 },
issn = { 0975-8887 },
pages = { 9-14 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume44/number6/6265-8418/ },
doi = { 10.5120/6265-8418 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:34:49.519404+05:30
%A H. B. Kekre
%A Sudeep Thepade
%A Rik Kamal Kumar Das
%A Saurav Ghosh
%T Image Classification using Block Truncation Coding with Assorted Color Spaces
%J International Journal of Computer Applications
%@ 0975-8887
%V 44
%N 6
%P 9-14
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The paper portrays comprehensive performance comparison of image classification techniques using block truncation coding (BTC) with assorted color spaces. Overall six color spaces have been explored which includes RGB color space for applying BTC to figure out the feature vector in Content Based Image Classification (CBIC) techniques. A generic database with 900 images having 100 images per category spread across 9 different categories have been considered to conduct the experimentation with the proposed Image Classification technique. On the whole nine hundred queries have been fired. The average success rate of class determination for each of the color spaces has been computed and considered for performance analysis. The results explicitly reveal performance improvement (higher average success rate values) with proposed color-BTC methods with luminance chromaticity color spaces compared to RGB color space. Best result is shown by YUV color space based BTC in content based image classification.

References
  1. Zakariya, S. M. , Ali, R. , & Ahmad, N. (2010). Combining Visual Features of an Image at Different Precision Value of Unsupervised Content Based Image Retrieval. Computational Intelligence and Computing Research (ICCIC)(2011)
  2. H. B. Kekre, Sudeep D. Thepade, "Image Retrieval using Augmented Block Truncation Coding Techniques", ACM International Conference on Advances in Computing, Communication and Control (ICAC3- 2009), pp. 384-390, 23-24 Jan 2009, Fr. Conceicao Rodrigous College of Engg. , Mumbai. Is uploaded on online ACM portal.
  3. H. B. kekre, Sudeep D. Thepade, "Improving Color to Gray and Back using Kekre's LUV Color Space", IEEE International Advanced Computing Conference 2009 (IACC?09), Thapar University, Patiala, INDIA, 6-7 March 2009. Is uploaded and available online at IEEE Xplore.
  4. Z. Zhang , W. Li & B. Li, "An Improving Technique of Color Histogram in Segmentation-based Image Retrieval. " 2009 Fifth International Conference on Information Assurance and Security,381-384(2009)
  5. R. Chakravarti, Meng Xiannong , "A Study of Color Histogram Based Image Retrieval," 2009 Sixth International Conference on Information Technology: New Generations, 2009. ITNG '09. , 1323-1328(2009)
  6. Dr. H. B. Kekre, Sudeep D. Thepade, "Image Retrieval using Non-Involutional Orthogonal Kekre?s Transform", International Journal of Multidisciplinary Research and Advances in Engineering (IJMRAE), Ascent Publication House, 2009, Volume 1, No. I, pp 189-203, 2009. Abstract available online at www. ascent-journals. com
  7. Maheshwari, M. , Silakari, S. , and Motwani, M. (2009). Image Clustering Using Color and Texture. 2009 First International Conference on Computational Intelligence Communication Systems and Networks,403-408.
  8. Dr. H. B. Kekre, Sudeep D. Thepade, "Image Retrieval using Color-Texture Features Extracted from Walshlet Pyramid", ICGST International Journal on Graphics, Vision and Image Processing (GVIP), Volume 10, Issue I, Feb. 2010, pp. 9-18, www. icgst. com/gvip/Volume10/Issue1/P1150938876. html
  9. Dr. H. B. Kekre, Tanuja K. Sarode, Sudeep D. Thepade, Vaishali Suryavanshi,"Improved Texture Feature Based Image Retrieval using Kekre?s Fast Codebook Generation Algorithm", Springer-International Conference on Contours of Computing Technology (Thinkquest-2010), Babasaheb Gawde Institute of Technology, Mumbai, 13-14 March 2010, The paper will be uploaded on online Springerlink.
  10. Wu Yanyan, Wu YIquan, "Shape-Based Image Retrieval Using Combining Global and Local Shape Features" 2nd International Congress on Image and Signal Processing, 2009. CISP '09. pp 1-5, 2009
  11. Dr. H. B. Kekre, Sudeep D. Thepade, "Boosting Block Truncation Coding using Kekre?s LUV Color Space for Image Retrieval", WASET Int. Journal of Electrical, Computer and System Engineering (IJECSE), Volume 2, Number 3, pp. 172-180, Summer 2008.
  12. Yung-Chen Chou, Hon-Hang Chang, "A High Payload Data Hiding Scheme for Color Image Based on BTC Compression Technique", Fourth International on Genetic and Evolutionary Computing (ICGEC), 2010 Conference
  13. Yung-Chen Chou, Hon-Hang Chang, "A Data Hiding Scheme for Color Image Based on BTC Compression Technique", 9th IEEE International Conference on Cognitive Informatics (ICCI), 2010, pp- 845 - 850
  14. Silakari, S. , Motwani, M. & Maheshwari, M. Color Image Clustering using Block Truncation Algorithm. International Journal of Computer Science 4, 2-6 (2009).
  15. Dr. H. B. Kekre, Sudeep D. Thepade, "Color Based Image Retrieval using Amendment Block Truncation Coding with YCbCr Color Space", International Journal on Imaging (IJI), Volume 2, Number A09, Autumn 2009, pp. 2-14. Available online at www. ceser. res. in/iji. html
  16. H. B. Kekre, Sudeep D. Thepade, "Image Blending in Vista Creation using Kekre's LUV Color Space", SPIT-IEEE Colloquium and International Conference, Sardar Patel Institute of Technology, Andheri, Mumbai, 04-05 Feb 2008.
  17. Dr. H. B. Kekre, Sudeep D. Thepade, "Color Traits Transfer to Grayscale Images", IEEE Int. Conf. on Emerging Trends in Engg. and Technology, ICETET-2008, 16-18 July 2008.
  18. Dr. H. B. Kekre, Sudeep D. Thepade, "Using YUV Color Space to Hoist the Performance of Block Truncation Coding for Image Retrieval", IEEE International Advanced Computing Conference 2009 (IACC?09), Thapar University, Patiala, INDIA, 6-7 March 2009.
  19. H. B. Kekre, Sudeep D. Thepade, Archana Athawale, Adib Parkar, "Using Assorted Color Spaces and Pixel Window Sizes for Colorization of Grayscale Images", ACM-International Conference and Workshop on Emerging Trends in Technology (ICWET 2010), Thakur College of Engg. And Tech. , Mumbai, 26-27 Feb 2010, The paper is uploaded on online ACM Portal.
  20. M. D. Fairchild, "Color Appearance Models. " Science 2nd, 385 (Addison Wesley Longman, Inc. 2005).
  21. H. B. Kekre, Sudeep D. Thepade, Adib Parkar, "A Comparison of Kekre?s Fast Search and Exhaustive Search for various Grid Sizes used for Colouring a Greyscale Image", 2nd International Conference on Signal Acquisition and Processing (ICSAP 2010), IACSIT, Bangalore, pp. 53-57, 9-10 Feb 2010, The paper is uploaded on online IEEE Xplore
  22. Image Database http://wang. ist. psu. edu/docs/related/Image. orig
Index Terms

Computer Science
Information Sciences

Keywords

Cbic Btc Color Space Rgb Kekre's Luv Ycbcr Yuv Yiq Kekre's Ycgcb