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Image Retrieval based on the combination of Color Histogram and Color Moment

by S. Mangijao Singh, K. Hemachandran
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 58 - Number 3
Year of Publication: 2012
Authors: S. Mangijao Singh, K. Hemachandran
10.5120/9263-3441

S. Mangijao Singh, K. Hemachandran . Image Retrieval based on the combination of Color Histogram and Color Moment. International Journal of Computer Applications. 58, 3 ( November 2012), 27-34. DOI=10.5120/9263-3441

@article{ 10.5120/9263-3441,
author = { S. Mangijao Singh, K. Hemachandran },
title = { Image Retrieval based on the combination of Color Histogram and Color Moment },
journal = { International Journal of Computer Applications },
issue_date = { November 2012 },
volume = { 58 },
number = { 3 },
month = { November },
year = { 2012 },
issn = { 0975-8887 },
pages = { 27-34 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume58/number3/9263-3441/ },
doi = { 10.5120/9263-3441 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:03:21.729747+05:30
%A S. Mangijao Singh
%A K. Hemachandran
%T Image Retrieval based on the combination of Color Histogram and Color Moment
%J International Journal of Computer Applications
%@ 0975-8887
%V 58
%N 3
%P 27-34
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

A novel technique for Content based image retrieval (CBIR) that employs color histogram and color moment of images is proposed. The color histogram has the advantages of rotation and translation invariance and it has the disadvantages of lack of spatial information. In this paper, to improve the retrieval accuracy, a content-based image retrieval method is proposed in which color histogram and color moment feature vectors are combined. For color moment, to improve the discriminating power of color indexing techniques, a minimal amount of spatial information is encoded in the color index by dividing the image horizontally into three equal non-overlapping regions. The three moments (mean, variance and skewness) are extracted from each region (in this case three regions), for all the color channels. Thus, for a HSV color space, 27 floating point numbers are used for indexing. The HSV (16, 4, 4) quantization scheme has been adopted for color histogram and an image is represented by a vector of 256-dimension. Weights are assigned to each feature respectively and calculate the similarity with combined features of color histogram and color moment using Histogram intersection distance and Euclidean distance as similarity measures. Experimental results show that the proposed method has higher retrieval accuracy in terms of precision than other conventional methods combining color histogram and color moments based on global features approach

References
  1. Xinjung, Z. 2006. "Research of Image retrieval based on color features", Liaoning technical University, 9(2), pp. 42-50.
  2. Datta, R. , Joshi, D. , Li, J. , Wang, J. Z. 2008. "Image retrieval: ideas, influences, and trends of the new age ", ACM Computing Surveys 40(2), pp 1-60.
  3. Gudivada, V. N. and Raghavan, V. V. 1995. "Content based image retrieval systems", IEEE Computer, Vol 28, No. 9, pp. 18-22.
  4. Manjunath, B. S. and Ma, W. Y. 1996. "Texture Features for browsing and retrieval of image data", IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 18, No. 8, pp. 837-842.
  5. Rui, Y. , Huang, T. S. , Ortega, M. and Mehrotra, S. 1998. " Relevance feedback : a power tool for interactive content based image retrieval ",IEEE Circuits and Systems for Video Technology , Vol. 8, No. 5, pp. 644-655.
  6. Swets, D. and Weng, J. 1999. "Hierarchical discriminant analysis for image retrieval", IEEE "PAMI, Vol. 21, No. 5, pp. 386-400.
  7. Zhang, H. and Zhong, D. 1995. "A scheme for visual feature based image retrieval", Proc. SPIE storage and retrieval for image and video databases.
  8. Yu-guang, Ye. 2007. "Research of image Retrieval based on fusing with multi-character", Hua Qiao University, pp. 14-16.
  9. Smeulders, A. M. , Worring, M. , Santini, S. , Gupta, A. and Jain, R. . 2000. "Content-based image retrieval at the end of the early years", IEEE Trans Pattern Anal Machine Intell 22: pp. 1349-1380.
  10. Choras, R. 2003. "Content-based image retrieval using color, texture, and shape information", In. Sanfeliu, Riuz-Shulcloper J. (eds) Progress in pattern recognition, speech and image analysis. Springer, Heidelberg.
  11. Corners, R. and Harlow, C. 1980. "A theoretical comparison of texture algorithms", IEEE Trans Pattern Anal Machine Intell 2: pp. 204-222.
  12. Howarth, P. and Ruger, S. "Evaluation of texture features for content based image retrieval", In: Enser P. et al. (eds) Image and video retrieval. Springer LNCS 3115:pp. 326-334.
  13. Swain, M. Z. and Ballard, D. H. 1992. "Color Indexing", Intl. J. of Computer Vision 7(1): pp. 11-32.
  14. Gonzalez, R. C. and Woods, R. C. 1992. Digital Image Processing, Addison-Weslel, Reading, MA.
  15. Mehtre, B. M. , Kankanhalli, M. S. , Narasimhalu, A. D. and Man, G. Ch. 1995. "Color matching for image retrieval", PRL, 16, pp. 325-331.
  16. Stricker, M. and Orengo, M. 1995. " Similarity of color images", In SPIE Conference on Storage and Retrieval for Image and Video Databases , volume 2420, pp. 381-392, San Jose, USA.
  17. Ogle, V. E. and Stonebraker, M. 1995. "Chabot: Retrieval from a relational database of images", Computer, pp. 40-48.
  18. Rui Y. and Huang, Th. S. 1999. "Image Retrieval: Current Techniques, Promising Directions and open Issues", JVCIR, vol. 10, pp. 39-62.
  19. Shih, J. L. and Chen, L. H. 2002. "Color image retrieval based on primitives of color moments", IEEE Proceedings online no. 20020614.
  20. Choras, R. S. , Andrysiak, T. and Choras, M. 2007. "Integrated color, texture and shape information for content-based image retrieval", Pattern Anal Applic. 10: 333-343.
  21. Xue, B. and Wanjun, L. 2009. "Research of Image Retrieval Based on Color", IEEE International Forum on Computer Science-Technology and Applications.
  22. Huang, Z. C. , Chan, P. P. K. , Ng, W. W. Y. , Yeung, D. S. 2010. "Content-based image retrieval using color moment and Gabor texture feature", in Poceedings of the IEEE Ninth International Conference on Machine Learning and Cybernetics, Qingdao, pp. 719-724.
  23. Kumar, D. K. , Sree, E. V. , Suneera, K. , Kumar, P. V. Ch. 2011. "Cotent Based Image Retrieval – Extraction by objects of user interest", International Journal of Computer Science and Engineering (IJCSE), Vol. 3, No. 3. , pp. 1068-1074.
  24. Saikrishna, T. V. , Yesubabu, A. , Anandrao, A. and Rani, T. S. 2012. "A Novel Image Retrieval Method using Segmentation and Color Moments", ACIJ, Advanced Computing:An International Journal, Vol. 3,No. 1, pp. 75-80.
  25. Dubey, R. S. , Choubey, R. , Bhattacharga, J. 2010. "Multi Feature Content Based Image Retrieval", (IJCSE) International Journal on Computer Science and Engineering, vol. 02, No. 06, pp. 2145-2149.
  26. Maheshwari, M. , Silakari, S. and Motwani, M. 2009. "Image Clustering using Color and Texture", Computational Intelligence, Communication Systems and Networks, pp. 403-408.
  27. Buch, P. P. , Vaghasia, M. V. and Machchchar, S. M. 2011. "Comparative analysis of content based image retrieval using both color and texture", Engineering(NUiCONE), Nirma University Internatonal Conference, pp. 1-4.
  28. Smith, J. 2002. " Color for Image Retrieval", Image Databases: Search and Retrieval of Digital Imagery, John Wiley & Sons, New York, pp. 285-311.
  29. Hafner, J. and Sawhney, H. S. 1995. "Efficient color histogram indexing for quadratic form distance functions", IEEE Transactions on Pattern Analysis and Machine Intelligence, 17(7), pp. 729-736.
Index Terms

Computer Science
Information Sciences

Keywords

CBIR color feature color histogram color moment Euclidean distance Canberra distance

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