Submit your paper : editorIJETjournal@gmail.com Paper Title : Content-Based Image Retrieval Research ISSN : 2395-1303 Year of Publication : 2022 10.5281/zenodo.7423753 MLA Style: - Abhinav Mishra, Shakti Gupta,Isha,Neha Yadav Content-Based Image Retrieval Research , Volume 8 - Issue 6 November - December 2022 International Journal of Engineering and Techniques (IJET) ,ISSN:2395-1303 , www.ijetjournal.org APA Style: - Abhinav Mishra, Shakti Gupta,Isha,Neha Yadav Content-Based Image Retrieval Research , Volume 8 - Issue 6 November - December 2022 International Journal of Engineering and Techniques (IJET) ,ISSN:2395-1303 , www.ijetjournal.org Abstract This study is produced with the goal of providing the most up-to-date review on CBIR development and image representation. From a low position grounding point in the back most in-depth semantic literacy styles, we anatomized the important colourful components of picture and image reclamation representative models. Important generalities and important exploration studies based on CBIR, and picture representation are discussed in depth, with advice for future research concluding with an invitation to continue exploring this location. Reference 1. G. Eason, B. Noble, and I. N. Sneddon, “On certain integrals of Lipschitz-Hankel type involving products of Bessel functions,” Phil. Trans. Roy. Soc. London, vol. A247, pp. 529–551, April 1955. (references) 2. D. Zhang, M. M. Islam, and G. Lu, “A review on automatic image annotation techniques,” Pattern Recognition, vol. 45, no. 1, pp. 346–362, 2012. 3. Y. Liu, D. Zhang, G. Lu, and W.-Y. Ma, “A survey of content-based image retrieval with high-level semantics,” Pattern Recognition, vol. 40, no. 1, pp.262–282, 2007. 4. T. Khalil, M. U. Akram, H. Raja, A. Jameel, and I. Basit, “Detection of glaucoma using cup to disc ratio from spectral domain optical coherence tomography images,” IEEE Access, vol. 6, pp. 4560–4576, 2018 5. W. Zhao, L. Yan, and Y. Zhang, “Geometric-constrained multi-view image matching method based on semi-global optimization,” Geo-Spatial Information Science, vol. 21, no. 2, pp. 115–126, 2018. [6] W. Zhou, H. Li, and Q. Tian, “Recent advance in content-based image retrieval: a literature survey,” 2017, https://arxiv. org/abs/1706. 06064.. 6. S. Susan, P. Agrawal, M. Mittal, and S. Bansal, “New shape descriptor in the context of edge continuity,” CAAI Transactions on Intelligence Technology, vol. 4, no. 2, pp. 101–109, 2019 7. S. Susan, P. Agrawal, M. Mittal, and S. Bansal, “New shape descriptor in the context of edge continuity,” CAAI Transactions on Intelligence Technology, vol. 4, no. 2, pp. 101–109, 2019 8. [9] R. Khan, C. Barat, D. Muselet, and C. Ducottet, “Spatial orientations of visual word pairs to improve bag-of-visual words model,” in Proceedings of the British Machine Vision Conference, pp. 89–91, BMVA Press, Surrey, UK, September 2012. 9. H. Anwar, S. Zambonini, and M. Kampel, “A rotation-in variant bag of visual words model for symbols based ancient coin classification,” in Proceedings of the 2014 IEEE International Conference on Image Processing (ICIP), pp. 5257–5261, IEEE, Paris, France, October 2014. 10. H. Anwar, S. Zambonini, and M. Kampel, “Efficient scale and rotation-invariant encoding of visual words for image classification,” IEEE Signal Processing Letters, vol. 22, no. 10, pp. 1762–1765, 2015. 11. Y. Liu, D. Zhang, and G. Lu, “Region-based image retrieval with high-level semantics using decision tree learning,” Pattern Recognition, vol. 41, no. 8, pp. 2554–2570, 2008. [13] M. M. Islam, D. Zhang, and G. Lu, “Automatic categorization of image regions using dominant colour-based vector quantization,” in Proceedings of the Digital Image Computing: Techniques and Applications, pp. 191–198, IEEE, Can Berra, Australia, December 2008. [14] A. Irtaza and M. A. Jaffar, “Categorical image retrieval through genetically optimized support vector machines (GOSVM) and hybrid texture features, “Signal, Image and Video Processing, vol. 9, no. 7, pp. 1503–1519, 2015. [15] D. Zhang and G. Lu, “Review of shape representation and description techniques,” Pattern Recognition, vol. 37, no. 1, pp. 1–19, 2004. Keywords — Image processing, Colour Features, Texture Features, Shape Features, Similarity Measures. |