A Review on Content Based Image RetrievalTechniques

Authors(3) :-Dahale Sunil V, Dr. S. B. Thorat, Dr. P. K. Butey

Content based image retrieval (CBIR) has been one of the furthermost significant research areas in computer science for the last period. A retrieval method which associations color and texture feature is proposed in this. Computer vision and digital image processing are valuable for content based image retrieval. Basically, computer vision systems try to retrieve an image to a user-defined description or pattern (e.g., shape sketch, image color etc.). The objective of computer vision is to provision image retrieval based on content properties like; shape, color, textures usually en coded in the form of feature vectors. In this paper following CBIR techniques discussed Relevance Feedback, Semantic Template, Wavelet Transform, Gabor Filter and Support Vector Machine.

Content-Based Image Retrieval (CBIR), Feature Extraction, Wavelets, Gabor, Vector Machine.

  1. Th.Gevers (2001). “Color Based Image Retriev-al” .Springer Verlag GmbH. pp.886-917
  2. M.J. Swain, D.H. Ballard (1991). “Color indexing” Int. J. Comput.Vis. 7 11-32.
  3. B.S. Manjunath and W.Y. Ma (1996). “Texture features for browsing and retrieval of image data”, IEEETrans. Pattern Anal. Mach. Intell, vol. 8, no. 8, pp. 837-842.
  4. M. N. Do and M. Vetterli (2002). “Wavelet-based texture retrieval using generalized Guassian density and Kullback-leibler distance”. IEEE Trans.Image Process,vol. 11, no. 2, pp. 146-158.
  5. Mvhammad hammad me mon!, jian-ping li!, Imran memon, Riaz ahmed shaikw and Farman alimangi,” Efficient Object Identification and Multiple Regions of Interest using CBIR Based on Relative Locations and Matching Regions”, 2015 ieee, pp: 247-250.
  6. Pushpalatha S. Nikkam, Dr. Nagaratna P. Hegde and Dr. B. Eswar Reddy,” Decomposition-Based Shape Template Matching for CBIR System”, 2015 IEEE International Conference on Computational Intelligence and Computing Research.
  7. CHAWKI Youness, EL ASNAOUI Khalid, OUANAN Mohammed and AKSASSE Brahim,” CBIR using the 2-D ESPRIT Method: Application to Coil_100 Database”, 2015 IEEE.
  8. Ekta Gupta and Rajendra Singh Kushwah,” Combination of Global and Local Features using DWT with SVM for CBIR”, 2015 IEEE.
  9. KAMLESH KUMAR, JIAN-PING LI and ZAINUL-ABIDIN,” COMPLEMENTARY FEATURE EXTRACTION APPROACH IN CBIR”,2015 IEEE, pp: 192-197
  10. Vrushali A. Wankhede and Prakash S. Mohod,” Content-based Image Retrieval from Videos using CBIR and ABIR algorithm”, 2015 IEEE, pp: 767-771.
  11. Radu Andrei Stefan, Ildikó-Angelica Szöke and Stefan Holban,” Hierarchical clustering techniques and classification applied in Content Based Image Retrieval (CBIR)”, 10th Jubilee IEEE International Symposium on Applied Computational Intelligence and Informatics • May 21-23, 2015 • Timis , oara, Romania, pp: 147-152.
  12. Satish Tunga, D. Jayadevappa and C. Gururaj,” A Comparative Study of Content Based Image Retrieval Trends and Approaches”, International Journal of Image Processing (IJIP), Volume (9) : Issue (3) : 2015, pp: 127-155.
  13. KattaSugamya,SureshPabboju, Dr.A.VinayaBabu, “A CBIR CLASSIFICATION USING SUPPORT VECTOR MACHINES” 978-1-4673-8810-8/16/$31.00 ©2016 IEEE [14]. Syntyche Gbèhounou, François Lecellier, Christine Fernandez-Maloigne, “Evaluation of local and global descriptors for emotional impact recognition”. 2016 Elsevier.
  14. Shu Wang, Jian Zhang, Senior Member, IEEE, Tony X. Han, Member, IEEE, and Zhenjiang Miao, Member, IEEE, “Sketch-Based Image Retrieval Through Hypothesis-Driven Object Boundary Selection With HLR Descriptor”, vol. 17, no. 7, pp 1045-1057, july 2015.
  15. K. Bozas and E. Izquierdo, “Large scale sketch based image retrieval using patch hashing,” Adv. Visual Comput., vol. 7431, pp. 210–219, 2012.
  16. R. Zhou, L. Chen, and L. Zhang, “Sketch-based image retrieval on a large scale database,” in Proc. 20th ACM Int. Conf. Multimedia, 2012,pp. 973–976.
  17. M. Eitz, K. Hildebrand, T. Boubekeur, and M. Alexa, “A descriptor for large scale image retrieval based on sketched feature lines,” in Proc. 6th Eurograph. Symp. Sketch-Based Interfaces Modeling, 2009, pp. 29–36.
  18. Priyanka Malode and Prof. S. V. Gumaste,” A Review Paper on Content Based Image Retrieval”, International Research Journal of Engineering and Technology (IRJET) Volume: 02 Issue: 09 | Dec-2015.
  19. Mohammed Alkhawlani, Mohammed Elmogy and Hazem El Bakry,” Text-based, Content-based, and Semantic-based Image Retrievals: A Survey”, International Journal of Computer and Information Technology (ISSN: 2279 – 0764) Volume 04 – Issue 01, January 2015, pp: 58-66.
  20. Pooja Devi, Mahesh Parmar, “A SURVEY ON CBIR TECHNIQUES AND LEARNING ALGORITHM COMPARISON”, International Journal of Latest Trends in Engineering and Technology Vol.(8)Issue(1), pp.197-205 DOI: http://dx.doi.org/10.21172/1.81.026 e-ISSN:2278-621X.

Publication Details

Published in : Volume 3 | Issue 5 | July-August 2017
Date of Publication : 2017-08-31
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 385-390
Manuscript Number : IJSRSET1734104
Publisher : Technoscience Academy

Print ISSN : 2395-1990, Online ISSN : 2394-4099

Cite This Article :

Dahale Sunil V, Dr. S. B. Thorat, Dr. P. K. Butey, " A Review on Content Based Image RetrievalTechniques, International Journal of Scientific Research in Science, Engineering and Technology(IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 3, Issue 5, pp.385-390, July-August-2017.
Journal URL : http://ijsrset.com/IJSRSET1734104

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