CFP last date
20 January 2025
Call for Paper
February Edition
IJCA solicits high quality original research papers for the upcoming February edition of the journal. The last date of research paper submission is 20 January 2025

Submit your paper
Know more
The week's pick
Responsive image
SFLA-Based Line Balancing and Task Optimization in Master-Slave Controlled Hanger Transportation Systems for Garment Production

Duc Hoang Nguyen
Random Articles
Reseach Article

Image Classification using Tag and Segmentation based Retrieval

by Shrikant Badghaiya, Atul Bharve
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 103 - Number 15
Year of Publication: 2014
Authors: Shrikant Badghaiya, Atul Bharve
10.5120/18151-9413

Shrikant Badghaiya, Atul Bharve . Image Classification using Tag and Segmentation based Retrieval. International Journal of Computer Applications. 103, 15 ( October 2014), 20-23. DOI=10.5120/18151-9413

@article{ 10.5120/18151-9413,
author = { Shrikant Badghaiya, Atul Bharve },
title = { Image Classification using Tag and Segmentation based Retrieval },
journal = { International Journal of Computer Applications },
issue_date = { October 2014 },
volume = { 103 },
number = { 15 },
month = { October },
year = { 2014 },
issn = { 0975-8887 },
pages = { 20-23 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume103/number15/18151-9413/ },
doi = { 10.5120/18151-9413 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:34:39.170100+05:30
%A Shrikant Badghaiya
%A Atul Bharve
%T Image Classification using Tag and Segmentation based Retrieval
%J International Journal of Computer Applications
%@ 0975-8887
%V 103
%N 15
%P 20-23
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In today's scenario when social media sites are widely used and high resolution images are shared. Tagging is an important approach for the retrieval of images in various applications. These are also used to manage personal media data. There are various techniques implemented for the image retrieval such as feature based, histogram based and transformation based but these techniques are not efficient in terms of classification ratio and accuracy. Here in this paper various tag based image technique are discussed so by analyzing the tag based image retrieval techniques a new proposed methodology can be implemented in the future.

References
  1. R. Veltkamp, H. Burkhardt, and H. -P. Kriegel. State-of-the-Art in Content-Based Image and Video Retrieval. Kluwer Academic Publishers, 2001.
  2. P. Howarth, A. Yavlinsky, D. Heesch, and S. M. Rger. Medical image retrieval using texture, locality and colour. In C. Peters, P Clough, J Gonzalo, G. J. F. Jones, M. Kluck, and B. Magnini, editors, Multilingual Information Access for Text, Speech and Images, 5th Workshop of the Cross-Language Evaluation Forum, pages 740–749, 2004.
  3. A. K. Jain and A. Vailaya. Image retrieval using color and shape. Pattern Recognition, 29(8):1233–1244, August 1996.
  4. J. Eakins and Margaret Graham, "Content based image retrieval," university of Northumbria at Newcastle.
  5. M. S. Lew, "Content-Based Multimedia Information Retrieval: State of the Art and Challenges," ACM Trans. Multimedia Computing, Comm. and Applications, vol. 2, pp. 1-19, 2006.
  6. L. Yang, R. Jin, L. Mummert, R. Sukthankar, A. Goode, B. Zheng, S. C. H. Hoi, and M. Satyanarayanan, "A Boosting Framework for Visuality-Preserving Distance Metric Learning and Its Application to Medical Image Retrieval," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 32, no. 1, pp. 30-44, Jan. 2010.
  7. L. Chen, D. Xu, I. W. Tsang, and J. Luo, "Tag-Based Web Photo Retrieval Improved by Batch Mode Re-Tagging," Proc. IEEE Conf. Computer Vision and Pattern Recognition, pp. 3440-3446, 2010.
  8. Y. Liu, D. Xu, I. W. Tsang, and J. Luo, "Textual Query of Personal Photos Facilitated by Large-Scale Web Data," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 33, no. 5 pp. 1022-1036, May 2011.
  9. Zhou X. S. , Thomas S. Huang "Unifying Keywords and Visual Contents in Image Retrieval", IEEE Multimedia, Vol. 9, Issue 2, April 2002 pages 23-33.
  10. Xirong Li, Cees G. M. Snoek, Marcel Worring, "Learning Social Tag Relevance by Neighbor Voting". IEEE TRANSACTIONS ON MULTIMEDIA, VOL. 11, NO. 7, NOVEMBER 2009.
  11. Y. Liu, R. Jin, and L. Yang, "Semi-Supervised Multi-Label Learning by Constrained Non-Negative Matrix Factorization," Proc. 21st Nat'l Conf. Artificial Intelligence, pp. 421-426, 2006.
  12. Lin Chen, Dong Xu, Ivor W. Tsang, and Jiebo Luo "Tag-Based Image Retrieval Improved by Augmented Features and Group-Based Refinement", IEEE Transactions On Multimedia, Vol. 14, No. 4, pp. 1057 – 1067, August 2012.
  13. Aixin Sun, Sourav S. Bhowmick, and Khanh Tran Nam Nguyen and Ge Bai "Tag-Based Social Image Retrieval: An Empirical Evaluation", Journal Of The American Society For Information Science And Technology, vol. 62, issue 12, pp. 2364–2381, 2011.
Index Terms

Computer Science
Information Sciences

Keywords

TBIR CBIR tag annotation AFSVM NDCG.

Powered by PhDFocusTM