Survey on Tag Based Image Search
Main Article Content
Abstract
Now a day's Flicker, Facebook is the popular social media websites. These sites are useful to the user to uploading their photos with free tags. There is need to develop a tag-based image search engine to find out the user-oriented images which are spread over the internet. The social re-ranking method is used for tag-based image search. The main goal is sorting the images according to their semantic information, social views and visual information. Each user uploads many images with different tags. The initial results are based on photos or images uploaded by different users. So first sort these images using the inter-user re-ranking method. Users that have higher uploaded images concerning the given query rank higher. Intra user re-ranking sorts these images based on ranked user set and find out related images from each user’s image set. The system gives better results using inverted index structure, visual feature, social views and semantic feature.
Article Details
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
IJCERT Policy:
The published work presented in this paper is licensed under the Creative Commons Attribution 4.0 International (CC BY 4.0) license. This means that the content of this paper can be shared, copied, and redistributed in any medium or format, as long as the original author is properly attributed. Additionally, any derivative works based on this paper must also be licensed under the same terms. This licensing agreement allows for broad dissemination and use of the work while maintaining the author's rights and recognition.
By submitting this paper to IJCERT, the author(s) agree to these licensing terms and confirm that the work is original and does not infringe on any third-party copyright or intellectual property rights.
References
D. Liu, X. Hua, L. Yang, M. Wang, and H. Zhang. Tag ranking. Proceedings of the IEEE International Conference on World Wide Web, 2009: 351-360.
M. Wang, K. Yang, X. Hua, and H. Zhang. Towards relevant and diverse search of social images. IEEE Transactions on Multimedia, 12(8):829-842, 2010.
G. Agrawal, R. Chaudhary. Relevancy tag ranking. In Computer and Communication Technology, pp. 169-173, IEEE, 2011.
L. Chen, D. Xu, I. Tsang. Tag-based image retrieval improved by augmented features and group-based refinement. Multimedia, IEEE
Transactions on, 14(4), 1057-1067, 2012.
L. Wu, R. Jin. Tag completion for image retrieval. Pattern Analysis and Machine Intelligence, IEEE Transactions on, 35(3), 716-727, 2013.
L. Chen, S. Zhu, Z. Li. Image retrieval via improved relevance ranking. In Control Conference, pp. 4620-4625, IEEE, 2014.
X. Qian, D. Hua, Y. Tang, and T. Mei, “social image tagging with diverse semanticsâ€, IEEE Trans. Cybernetics, vol.44, no. 12, 2014, pp. 2493-2508.
XuemingQian, Yisi Zhao, Junwei Han: Image Location Estimation by Salient Region Matching. IEEE Transactions on Image Processing 24(11): 4348-4358 (2015)
X.Qian, D. Lu, X. Liu, “Tag based image retrieval by user-oriented rankingâ€. Proceedings of International Conference on Multimedia Retrieval.ACM, 2015.
10. X. Qian, y. Xue, Y. Tang, X. Hou.â€Landmark Summarization with Diverse Viewpointsâ€, IEEE Trans. Circuits and Systems for Video Technology, 2015
11. Xueming Qian, Dan Lu, Xiaoxiao Liu. Tag Based Image Search by Social Re-ranking. IEEE Transactions on, Multimedia 2016.
Ajin P Thomas, Sruthi P.S, Jerry Rachel Jacob, Vandana V Nair, Reeba R,‖ Survey on Different Applications of Image Processing.‖ International Journal of Computer Engineering In Research Trends.,vol.4,no.2,pp. 13-19,2017.
Trisha Chakraborty, Nikita Nalawade, Abhishri Manjre, Akanksha Sarawgi, Pranali P Chaudhari,‖ Review of Various Image Processing Techniques for Currency Note Authentication.‖ International Journal of Computer Engineering In Research Trends.,vol.3,no.3,pp. 119-122,2016.
Gunjan, Er. Madan Lal,‖ Investigation of Various Image Steganography Techniques in Spatial Domain.‖ International Journal of Computer Engineering In Research Trends., vol.3,no.6,pp. 347-351,2016.
G.Prasanthi, A.Somasekhar,‖ Anti-Theft Tracking and Controlling Of Vehicle According Us.‖ International Journal of Computer Engineering In Research Trends., vol.2, no.12, pp. 898-903, 2015.