Have a personal or library account? Click to login
Efficient Content-Based Image Retrieval System with Two-Tier Hybrid Frameworks Cover

Efficient Content-Based Image Retrieval System with Two-Tier Hybrid Frameworks

Open Access
|Jan 2023

References

  1. [1] T. Kato, “Database architecture for content-based image retrieval”, in Image Storage and Retrieval Systems, vol. 1662, A. A. Jamberdino and C. W. Niblack, Eds. International Society for Optics and Photonics, 1992, pp. 112–123. https://doi.org/10.1117/12.58497
  2. [2] J. P. Eakins and M. E. Graham, “Content-based image retrieval: A report to the JISC technology applications programme,” Institute for Image Data Research, University of Northumbria at Newcastle, 1999.
  3. [3] M. S. Lew, N. Sebe, C. Djeraba, and R. Jain, “Content-based multimedia information retrieval: State of the art and challenges,” ACM Transactions on Multimedia Computing, Communications, and Applications, vol. 2, no. 1, pp. 1–19, Feb. 2006. https://doi.org/10.1145/1126004.1126005
  4. [4] R. C. Veltkamp, M. Tanase, and D. Sent, “Features in content-based image retrieval systems: A survey,” in State-of-the-Art in Content-Based Image and Video Retrieval, vol. 22, R. C. Veltkamp, H. Burkhardt, and H. P. Kriegel, Eds. Dordrecht: Springer Netherlands, pp. 97–124, 2001. https://doi.org/10.1007/978-94-015-9664-0_5
  5. [5] N. Arunkumar and A. Ranjith Ram, “CBIR systems: Techniques and challenges,” in 2020 International Conference on Communication and Signal Processing (ICCSP), Chennai, India, Jul. 2020, pp. 0141–0146. https://doi.org/10.1109/ICCSP48568.2020.9182323
  6. [6] H. Liu, W. Wang, and P. Jiao, “Content based image retrieval via sparse representation and feature fusion,” in 2019 IEEE 8th Data Driven Control and Learning Systems Conference (DDCLS), Dali, China, May 2019, pp. 18–23. https://doi.org/10.1109/DDCLS.2019.8908926
  7. [7] M. Kokare, B. N. Chatterji, and P. K. Biswas, “A survey on current content based image retrieval methods,” IETE Journal of Research, vol. 48, no. 3–4, pp. 261–271, Mar. 2002. https://doi.org/10.1080/03772063.2002.11416285
  8. [8] H. Atlam, G. Attiya, and N. El-Fishawy, “Integration of color and texture features in CBIR system,” International Journal of Computer Applications, vol. 164, no. 3, pp. 23–29, Apr. 2017. https://doi.org/10.5120/ijca2017913600
  9. [9] F. Long, H. Zhang, and D. D. Feng, “Fundamentals of content-based image retrieval,” in Multimedia Information Retrieval and Management: Technological Fundamentals and Applications, D.D. Feng, W.C. Siu, and H.J. Zhang, Eds. Springer Berlin Heidelberg, 2003, pp. 1–26. https://doi.org/10.1007/978-3-662-05300-3_1
  10. [10] P. Saxena and Shefali, “Content based image retrieval system by fusion of color, texture and edge features with SVM classifier and relevance feedback,” International Journal of Research -GRANTHAALAYAH, vol. 6, no. 9, pp. 259–273, Sep. 2018. https://doi.org/10.29121/granthaalayah.v6.i9.2018.1230
  11. [11] Afshan Latif et al., “Content-based image retrieval and feature extraction: A comprehensive review,” Mathematical Problems in Engineering, vol. 2019, Art. no. 9658350, Aug. 2019. https://doi.org/10.1155/2019/9658350
  12. [12] A. Tiwari and V. Bansal, “Patseek: Content based image retrieval system for patent database,” in The Fourth International Conference on Electronic Business – Shaping Business Strategy in a Networked WorldAt, Beijing, China, 2004, pp. 1167–1171.
  13. [13] C. Vasanthanayaki and R. Malini, “An enhanced content based image retrieval system using color features,” International Journal of Engineering and Computer Science, vol. 2, no. 12, pp. 3465–3471, 2013.
  14. [14] K. Bharathi and M. C. Mohan, “Content based image retrieval: An overview of architecture, challenges and issues,” International Journal of Engineering Research in Computer Science and Engineering, vol. 4, no. 12, 2017.
  15. [15] A. Arampatzis, K. Zagoris, and S. A. Chatzichristofis, “Dynamic two-stage image retrieval from large multimedia databases”, Information Processing and Management, vol. 49, no. 1, pp. 274–285, Jan. 2013. https://doi.org/10.1016/j.ipm.2012.03.005
  16. [16] P. Vadivel, D. Yuvaraj, S. Krishnan, and S. R. Mathusudhanan, “An efficient CBIR system based on color histogram, edge, and texture features,” Concurrency and Computation: Practice and Experience, vol. 31, no. 12, Art. no. e4994, 2018. https://doi.org/10.1002/cpe.4994
  17. [17] O. A. B. Penatti, E. Valle, R. da S. Torres, “Comparative study of global color and texture descriptors for web image retrieval,” Journal of Visual Communication and Image Representation, vol. 23, no. 2, pp. 359–380, Feb. 2012. https://doi.org/10.1016/j.jvcir.2011.11.002
  18. [18] A. Moghimian, M. Mansoorizadeh, and M.H. Dezfoulian, “Content based image retrieval using fusion of multilevel bag of visual words,” SN Applied Sciences, vol. 1, pp. 1735, Nov. 2019. https://doi.org/10.1007/s42452-019-1793-5
  19. [19] N. Shrivastava and V. Tyagi, “Multistage content-based image retrieval,” in 2012 CSI Sixth International Conference on Software Engineering (CONSEG), Indore, India, Sep. 2012, pp. 1–4. https://doi.org/10.1109/CONSEG.2012.6349469
  20. [20] M. Alkhawlani, M. Elmogy, and H. El-Bakry, “Text-based, content-based, and semantic-based image retrievals: A survey,” International Journal of Computer and Information Technology, vol. 4, pp. 58–66, 2015.
  21. [21] J. Li and J. Z. Wang, “Automatic linguistic indexing of pictures by a statistical modeling approach,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 25, no. 9, pp. 1075–1088, Sep. 2003. https://doi.org/10.1109/TPAMI.2003.1227984
  22. [22] J. Z. Wang, J. Li, and G. Wiederhold, “Simplicity: semantics-sensitive integrated matching for picture libraries,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 23, no. 9, pp. 947–963, Sep. 2001. https://doi.org/10.1109/34.955109
  23. [23] Y. Mistry and D. Ingole, “Survey on content based image retrieval systems,” International Journal of Innovative Research in Computer and Communication Engineering, vol. 2, pp. 1827–1836, 2013.
  24. [24] R. Hirwane, “Fundamental of content-based image retrieval, ” International Journal of Computer Science and Information Technologies, vol. 3, no. 1, pp. 3260–3263, 2012.
  25. [25] F. Malik and B. Baharudin, “Analysis of distance metrics in content-based image retrieval using statistical quantized histogram texture features in the DCT domain,” Journal of King Saud University – Computer and Information Sciences, vol. 25, no. 2, pp. 207–218, Jul. 2013. https://doi.org/10.1016/j.jksuci.2012.11.004
  26. [26] S. Pabboju, and V. G. Reddy, “A novel approach for content-based image indexing and retrieval system using global and region features,” International Journal of Computer Science and Network Security, vol. 9, no. 2, pp. 119–130, 2009.
  27. [27] A. Irtaza, A. Jaffar, E. Aleisa, and T. S. Choi, “Embedding neural networks for semantic association in content-based image retrieval,” Multimedia Tools and Applications, vol. 72, pp. 1911–1931, May 2014. https://doi.org/10.1007/s11042-013-1489-6
  28. [28] X. Tian, L. Jiao, X. Liu, and X. Zhang, “Feature integration of eodh and color-sift: Application to image retrieval based on codebook,” Signal Processing: Image Communication, vol. 29, no. 4, pp. 530–545, Apr. 2014. https://doi.org/10.1016/j.image.2014.01.010
  29. [29] N. Ali et al. “A novel image retrieval based on visual words integration of SIFT and SURF,” PLoS ONE, vol. 11, no. 6, Art. no. e0157428, Jun. 2016. https://doi.org/10.1371/journal.pone.0157428491211327315101
  30. [30] M. E. Elalami, “A new matching strategy for content-based image retrieval system,” Applied Soft Computing, vol. 14, no. C, pp. 407–418, Jan. 2014. https://doi.org/10.1016/j.asoc.2013.10.003
  31. [31] S. Zeng, R. Huang, H. Wang, and Z. Kang, “Image retrieval using spatiograms of colors quantized by gaussian mixture models,” Neuro Computing, vol. 171, pp. 673–684, Jan. 2016. https://doi.org/10.1016/j.neucom.2015.07.008
DOI: https://doi.org/10.2478/acss-2022-0018 | Journal eISSN: 2255-8691 | Journal ISSN: 2255-8683
Language: English
Page range: 166 - 182
Published on: Jan 24, 2023
In partnership with: Paradigm Publishing Services
Publication frequency: Volume open

© 2023 Fatima Shaheen, R. L. Raibagkar, published by Riga Technical University
This work is licensed under the Creative Commons Attribution 4.0 License.