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Reseach Article

A New Approach for Enhancing Image Retrieval using Neutrosophic Sets

by Mohamed Eisa
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 95 - Number 8
Year of Publication: 2014
Authors: Mohamed Eisa

Mohamed Eisa . A New Approach for Enhancing Image Retrieval using Neutrosophic Sets. International Journal of Computer Applications. 95, 8 ( June 2014), 12-20. DOI=10.5120/16613-6453

@article{ 10.5120/16613-6453,
author = { Mohamed Eisa },
title = { A New Approach for Enhancing Image Retrieval using Neutrosophic Sets },
journal = { International Journal of Computer Applications },
issue_date = { June 2014 },
volume = { 95 },
number = { 8 },
month = { June },
year = { 2014 },
issn = { 0975-8887 },
pages = { 12-20 },
numpages = {9},
url = { },
doi = { 10.5120/16613-6453 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
%0 Journal Article
%1 2024-02-06T22:18:53.209267+05:30
%A Mohamed Eisa
%T A New Approach for Enhancing Image Retrieval using Neutrosophic Sets
%J International Journal of Computer Applications
%@ 0975-8887
%V 95
%N 8
%P 12-20
%D 2014
%I Foundation of Computer Science (FCS), NY, USA

This paper adopts a novel model for Content-Based Image Retrieval (CBIR) system depending on an excellent segmentation strategy and combination of Visual Descriptors (VDs). The presented model is divided into four main phases: image segmentation, visual descriptors, Dimensionality Reduction (DR) and similarity matching. An improved segmentation technique based on Neutrosophic Sets (NSs) is proposed and applied to see their ability and accuracy to segment images. In relative to the VDs, the geometrical moments are used to extract the shape of an object, the modified Stricker method to the color extraction is proposed and the MPEG-7 edge histogram descriptor is presented for each of them. Experimental results presented show that the proposed model provides precise image retrieval in a short time.

  1. Guoping Qiu et al. , Visual guided navigation for image retrieval, Pattern Recognition 40(6), 2007, 1711–1721.
  2. V. P. Subramanyam, S. K. Sett, Knowledge-based image retrieval system, Knowledge-Based Systems 21(2), 2008, 89–100.
  3. Veltkamp R. C. , Tanase M. : Content-Based Image Retrieval Systems: A Survey. Revised and extended version of Technical Report UU-CS-2000-34, Department of Computing Science, Utrecht University, 2002.
  4. F. Smarandache,"A Unifying Field in Logics Neutrosophic Logic". Neutrosophy, Neutrosophic Set, Neutrosophic Probability, third ed: American Research Press, 2003.
  5. H. D. Cheng, Y. guot, and y. zhang, A novel image segmentation approach based on neutrosophic set and improved fuzzy c-means algorithm, world scientific publishing company, new math. and natural computation, vol. 7, no. 1, 155-171, 2011.
  6. J. Mohan, V. Krishnaveni, Y. Guo, A new neutrosophic approach of wiener Filtering for MRI denoising, measurement science review, Vol. 13, No. 4, 177-186, 2013.
  7. S. L. Phung, Abdesselam Bouzerdoum, 2007: Detecting people in images: An Edge Density Approach, IEEE, ICASSP, 1229-1232.
  8. S. Min, S. Park, and C. Won, "Image Retrieval via Query-by- Layout using MPEG-7 Visual Descriptors" ETRI Journal, Vol. 29, No. 2, 2007.
  9. M. Eom, Y. Choe, "Fast Extraction of Edge Histogram in DCT Domain based on MPEG-7" PWASET Vol. 9, 2005.
  10. J. Wei, E. Guihua, D. Qionghai, G. Jinwei, Similarity online feature selection in content-based image retrieval, IEEE Transactions on Image Processing 15(3), 2006, 702–712.
  11. F. Smarandache, "A Unifying Field in Logics Neutrosophic Logic". Neutrosophy, Neutrosophic Set, Neutrosophic Probability, third ed: American Research Press, 2003.
  12. Ming Zhang, Ling Zhang, H. D. Cheng, "A neutrosophic approach to image segmentation based on watershed method", Elsevier Signal Processing 90, 1510–1517, 2010.
  13. H. D. Cheng, Y. Guot, Y. Zhang, "A Novel Image Segmentation Approach Based on Neutrosophic Set And Improved Fuzzy C-Means Algorithm", World Scientific Publishing Company, New Math. and Natural Computation, Vol. 7, No. 1, 155-171, 2011.
  14. Y. Guo, H. D. Cheng, Y. Zhang, W. Zhao, "A new neutrosophic appraoch to image thresholding", Atlantis Press, Proceedings of the 11th Joint Conference on Information Sciences, 1-6, 2008.
  15. A. Ahirwar, "Study of Techniques used for Medical Image Segmentation and Computation of Statistical Test for Region Classification of Brain MRI", I. J. Information Technology and Computer Science, 05, 44-53, 2013.
  16. Preeti Aggarwal, H. K. Sardana, Gagandeep Jindal, Content-Based Medical Image Retrieval: Theory, Gaps and Future Directions, ICGST-GVIP Journal, Vol. 9, Issue (II), April 2009.
  17. M. J. Swain and D. H. Ballard, "Color Indexing", International Journal of Computer Vision, Vol. 7, No. 1, 11-32, 1991.
  18. B. Funt and G. Finlayson, "Color Constant Color Indexing" IEEE Trans. Pattern Analysis and Machine Intelligence, Vol. 17, No. 5, 522-529, 1995.
  19. M. Stricker and M. Orengo, "Similarity of color Images" SPIE, Vol. 220, No. 1, 381-392, 1995.
  20. B. S. Manjunath, P. Salembier, T. Sikora, "Introduction to MPEG-7", JOHN WILLEY&SONS, LTD, 183-184, 2002.
  21. W. Pedrycz and George Vukovich "Feature analysis through information granulation and fuzzy sets" ARTICLE Pattern Recognition, Volume 35, Issue 4, April 2002, 825-834.
  22. M. A. Berry and Gordon Linoff, "Mastering Data Mining the Art and Science of Customer Relationship Management" Wiley computer publishing, John Wiley & Sons, Inc. 2000.
  23. R. M. Hogarth. "Methods for Aggregating Opinions", In H. Jungermann and G. De Zeeuw, Editors, Decision Making and Change in Human Affairs. D. Reidel Publishing, Dordrecht-Holland, 1977.
  24. C. Salton and C. Buckley "Improving Retrieval Performance by Relevance Feedback" the research report of Cornell University, 1-24, 1988.
  25. C. Won, D. Park, and S. Jun, "Efficient Use of MPEG-7 Edge Histogram Descriptor" ETRI Journal, Vol. 24, No. 1, 2002.
  26. Mohamed Eisa, Ibrahim El-Henawy, A. E. Elalfi and Hans Burkhardt "Image Retrieval based on Invariant Features and Histogram Refinement" ICGST International Conference on Graphics, Vision and Image Processing, GVIP 05 Conference, 19-21 Dec. 2005, CICC, Cairo, Egypt.
  27. Ibrahim El-Henawy, Mohamed Eisa, A. E. Elalfi and Hans Burkhardt "Image Retrieval using Local Color and Texture Features" ICGST International Journal on Graphics, Vision and Image Processing (GVIP), May. 2005, Vol. SI1, Pages 47-52.
  28. Corel Corporation. URL: http://www. corel. com/ (2005)
  29. ISO/IEC/JTC1/SC29/WG11: "Description of Core Experiments for MPEG-7 Color/Texture Descriptors," MPEG document N2929, Melbourne, 1999.
Index Terms

Computer Science
Information Sciences


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