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Year 2021, Volume: 5 Issue: 1, 123 - 141, 15.04.2021
https://doi.org/10.35860/iarej.811927

Abstract

References

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An analysis of content-based image retrieval

Year 2021, Volume: 5 Issue: 1, 123 - 141, 15.04.2021
https://doi.org/10.35860/iarej.811927

Abstract

Nowadays, working on digital images is gaining much popularity in multimedia systems, due to the rapid increase in the utilization of large image databases. Thus, the Content-Based Image Retrieval (CBIR) method has become the most valuable method for these databases. This study mainly focuses on content-based image retrieval; which uses image features like color, shape, texture, etc. by searching the user query image from a large image database based on user request. CBIR is the most widely used technique as its searching capability is faster than the other traditional methods, and it works well in retrieving images automatically. It is also a big alternative approach to traditional methods. The CBIR techniques are used in many applications like surveillance detection, crime avoidance, fingerprint identification, E-library, medical, historical monument and biodiversity information systems, and many more. A total of 38 CBIR articles were comparatively analyzed.

References

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  • 4. Lowe, D.G., Distinctive Image Features from Scale-Invariant Keypoints. International Journal of Computer Vision, 2004. 60(2): p. 91-110.
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  • 10. Jenni, K., S. Mandala, and M.S. Sunar, Content Based Image Retrieval Using Colour Strings Comparison. Procedia Computer Science, 2015. 50: p. 374-379.
  • 11. Liu, M., L. Yang, and Y. Liang, A chroma texture-based method in color image retrieval.Optik, 2015. 126(20): p. 2629-2633.
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There are 86 citations in total.

Details

Primary Language English
Subjects Software Engineering (Other)
Journal Section Review Articles
Authors

Hakan Koyuncu 0000-0002-8444-1094

Manish Dixit This is me 0000-0003-2589-6010

Baki Koyuncu This is me 0000-0002-0507-3431

Publication Date April 15, 2021
Submission Date October 20, 2020
Acceptance Date February 12, 2021
Published in Issue Year 2021 Volume: 5 Issue: 1

Cite

APA Koyuncu, H., Dixit, M., & Koyuncu, B. (2021). An analysis of content-based image retrieval. International Advanced Researches and Engineering Journal, 5(1), 123-141. https://doi.org/10.35860/iarej.811927
AMA Koyuncu H, Dixit M, Koyuncu B. An analysis of content-based image retrieval. Int. Adv. Res. Eng. J. April 2021;5(1):123-141. doi:10.35860/iarej.811927
Chicago Koyuncu, Hakan, Manish Dixit, and Baki Koyuncu. “An Analysis of Content-Based Image Retrieval”. International Advanced Researches and Engineering Journal 5, no. 1 (April 2021): 123-41. https://doi.org/10.35860/iarej.811927.
EndNote Koyuncu H, Dixit M, Koyuncu B (April 1, 2021) An analysis of content-based image retrieval. International Advanced Researches and Engineering Journal 5 1 123–141.
IEEE H. Koyuncu, M. Dixit, and B. Koyuncu, “An analysis of content-based image retrieval”, Int. Adv. Res. Eng. J., vol. 5, no. 1, pp. 123–141, 2021, doi: 10.35860/iarej.811927.
ISNAD Koyuncu, Hakan et al. “An Analysis of Content-Based Image Retrieval”. International Advanced Researches and Engineering Journal 5/1 (April 2021), 123-141. https://doi.org/10.35860/iarej.811927.
JAMA Koyuncu H, Dixit M, Koyuncu B. An analysis of content-based image retrieval. Int. Adv. Res. Eng. J. 2021;5:123–141.
MLA Koyuncu, Hakan et al. “An Analysis of Content-Based Image Retrieval”. International Advanced Researches and Engineering Journal, vol. 5, no. 1, 2021, pp. 123-41, doi:10.35860/iarej.811927.
Vancouver Koyuncu H, Dixit M, Koyuncu B. An analysis of content-based image retrieval. Int. Adv. Res. Eng. J. 2021;5(1):123-41.



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