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Content based Image Retrieval System with Watermarks and Relevance Feedback

by Sebin Jose, Philumon Joseph
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 99 - Number 11
Year of Publication: 2014
Authors: Sebin Jose, Philumon Joseph
10.5120/17414-8197

Sebin Jose, Philumon Joseph . Content based Image Retrieval System with Watermarks and Relevance Feedback. International Journal of Computer Applications. 99, 11 ( August 2014), 1-6. DOI=10.5120/17414-8197

@article{ 10.5120/17414-8197,
author = { Sebin Jose, Philumon Joseph },
title = { Content based Image Retrieval System with Watermarks and Relevance Feedback },
journal = { International Journal of Computer Applications },
issue_date = { August 2014 },
volume = { 99 },
number = { 11 },
month = { August },
year = { 2014 },
issn = { 0975-8887 },
pages = { 1-6 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume99/number11/17414-8197/ },
doi = { 10.5120/17414-8197 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:27:54.493381+05:30
%A Sebin Jose
%A Philumon Joseph
%T Content based Image Retrieval System with Watermarks and Relevance Feedback
%J International Journal of Computer Applications
%@ 0975-8887
%V 99
%N 11
%P 1-6
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Image retrieval and related operations are always a 'hotspot' in the information era. Content-based image retrieval (CBIR) is a vastly developing area in the multimedia technology domain. To enhance security, we apply watermarking technique into the retrieval system and propose an approach for JEPG image retrieval. The proposed image retrieval system consists of three main phases, offline process, online retrieval process and the feedback process. The offline process aims at the feature vector extraction from the image. Later these features will be stored in the database. When it comes to the online retrieval process, it actually extracts the image features from the input image and matches these feature vectors with those available in the image database. In order to overcome the possible dissimilarity between bottom features and high-level semantics in the image retrieval; we introduce the feedback network to strengthen the retrieval efficiency. This is a simple categorized screening. Such a feedback scenario makes the system more user-friendly and effective. The proposed feedback screening strategy filters the images from irrelevant categories and enriches the final result with more relevant images

References
  1. Color Image Retrieval System Based on Shape and Texture Watermarks : Hao Zhang, Hua Chen, Fa-Xin Yu and Zhe- Ming Lu
  2. C. W. Niblack, R. Barber, W. Equitz, M. D. Flickner, E. H. Glasman, D. Pektovic, P. Yanker, C. Faloutsos, and G. Taubin, The QBIC Project: Querying Images by Content Using Color, Texture, and Shape," in: Proc. of Storage and Retrieval for Image and Video Databases, SPIE, vol. 1908, no. 1, pp. 173187, 1993.
  3. Image Retrieval Using ESNs and Relevance Feedback Yuanfeng Yang,JiangSu Province Support Software Engineering R&D Center for Modern Information Technology Application in Enterprise Suzhou, China, 215104
  4. Information Hiding in Image Retrieval Systems,S. Areepongsa, N. Kaewkamnerd, Y. F. Syed, and K. R. Rao
  5. Quantization Index Modulation: A Class of Provably Good Methods for Digital Watermarking and Information Embedding , Brian Chen, Member, IEEE, and Gregory W. Wornell, Senior Member, IEEE
  6. A survey on content based image retrieval ,Dharani, T. ; Dept. of Comput. Sci. , Periyar Univ. , Salem, India ; Aroquiaraj, I. L. 2013 International Conference on Pattern Recognition, Informatics and Mobile Engineering (PRIME)
  7. Fusion of colour, shape and texture features for content based image retrieval,Anantharatnasamy, P. ; Dept. of Comput. Eng. , Univ. of Peradeniya, Peradeniya, Sri Lanka ; Sriskandaraja, K. ; Nandakumar, V. ; Deegalla, S. 2013 8th International Conference on Computer Science & Education (ICCSE)
  8. Content-Based Image Retrieval Using Invariant Color and Texture Features ,Afifi, A. J. ; Comput. Eng. Dept. , Islamic Univ. of Gaza, Gaza, Palestinian Authority ; Ashour, W. M. 2012 International Conference on Digital Image Computing Techniques and Applications (DICTA)
  9. A novel public digital watermarking for still images based on encryption algorithm,Gwo-Chin Tai ; Dept. of Comput. Sci. , Nat. Tsing Hua Univ. , Hsinchu, Taiwan ; Long-Wen Chang IEEE 37th Annual 2003 International Carnahan Conference on Security Technology, 2003. Proceedings.
  10. A near reversible image watermarking algorithm,Bin Zhang ; Key Lab. of Network & Inf. Attack & Defence Technol. of MOE, Beijing Univ. of Posts & Telecommun. , Beijing, China ; Yang Xin ; Xin-Xin Niu ; Kai-Guo Yuan 2010 International Conference on Machine Learning and Cybernetics (ICMLC)
  11. A Similarity Measuring Method for Images Based on the Feature Extraction Algorithm using Reference Vectors,Ohno, A. ;Kobe Univ. Tsurukabuto, Kobe ; Murao, H. ICICIC '07. Second International Conference on Innovative Computing, Information and Control, 2007.
  12. Image indexing using color correlograms , Jing Huang Cornell Univ. , Ithaca, NY, USA Kumar, S. R. ; Mitra, M. ; Wei- Jing Zhu ; Zabih, R.
  13. J. R. Smith and S. F. Chang, VisualSEEk: a fully automated content-based image query system, ACM Multimedia, Boston, MA. , pp. 87-98, Nov. 1996.
  14. Y. Rui, T. S. Huang and S. Chang, Image Retrieval: current techniques, promising directions, and open issues, J. Visual Communication and Image Representation, vol. 10, pp. 39- 62, March 1999.
  15. S. Areepongsa and K. R. Rao, Invariant features for texture image retrieval using steerable pyramid, WPMC 2000, Bangkok, Thailand, Nov. 2000.
  16. H. Mller, W. Mller, D. Squire, S. Marchand-Maillet, and T. Pun, Performance Evaluation in Content-based Image Retrieval: Overview and Proposals, Pattern Recognition Letters, vol. 22, no. 5, pp. 593601, Apr. 2001.
  17. X. L. Li, Watermarking in Secure Image Retrieval, Patten Recognition Letters, vol. 24,no. 14, pp. 24312434, Oct. 2003.
Index Terms

Computer Science
Information Sciences

Keywords

Content Image

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