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F- Norm based Color Image Retrieval with Selective Relevance Feedback

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International Journal of Computer Applications
© 2013 by IJCA Journal
Volume 67 - Number 22
Year of Publication: 2013
Authors:
Jayashree Khanapuri
10.5120/11530-7373

Jayashree Khanapuri. Article: F- Norm based Color Image Retrieval with Selective Relevance Feedback. International Journal of Computer Applications 67(22):38-42, April 2013. Full text available. BibTeX

@article{key:article,
	author = {Jayashree Khanapuri},
	title = {Article: F- Norm based Color Image Retrieval with Selective Relevance Feedback},
	journal = {International Journal of Computer Applications},
	year = {2013},
	volume = {67},
	number = {22},
	pages = {38-42},
	month = {April},
	note = {Full text available}
}

Abstract

Image retrieval has become an important aspect in today's world as there is rapid growth of digital data day by day. It is required to have efficient search system with fast and accurate retrieval to cater to the need of end user with less computational cost and time. A new content based search system is required to address the problem. In this paper, a new method is proposed for color image analysis and retrieval based on F-norm theory is presented. Image Retrieval is carried out by the decomposition of images using complex wavelet transform and extracting the features of the image from low frequency channel using F-norm theory. A new way is suggested to further enhance the performance of the system with relevance feedback in which retrieval is carried by training only the selected query images from the database having poor retrieval accuracy.

References

  • Dr. Fuhui long, Dr. Hong jiang and Prof. David Dagan Feng, Fundamentals Of Content-Based Image Retrieval. Chapter 1, (10-Apr-2003) Multimedia Information Retrieval and Management: Technological Fundamentals, Springer.
  • Kuo-An Wang, Hsuan-Hung Lin, Po-Chou Chan, Chuen-Horng Lin, Shih-Hsu Chang, Yung-Fu Chen, June 2008. Implementation of an Image Retrieval System Using Wavelet Decomposition and Gradient Variation, ISSN: 1109-2750, Issue 6, Volume 7. , 724-73
  • P. S. Hiremath, S. Shivashankar and Jagadeesh Pujari September 2006, Wavelet Based Features for Color Texture Classification With Application To CBIR, IJCSNS International Journal of Computer Science and Network Security, VOL. 6 No. 9. ,124-133
  • G. Paschos, 1998. Chromatic Correlation Features for Texture Recognition, Pattern Recognition Letters, 19:643-50.
  • G. Paschos, 2000. Fast Color Texture Recognition using Chromaticity Moments, Pattern Recognition Letters, 21:837-41.
  • G. Van de Wouver, P. Scheunders, S. Livens, D. V. Dyck 1999, Wavelet correlation signatures for color texture characterization, Pattern recognition Letters, 32:443-51.
  • M. P. Dubuisson, Jolly A. Gupta, 2000. Color and Texture Fusion: application to aerial image segmentation and GIS updating,, Image and Vision computing, 18: 823-32.
  • A. Drimbean, P F Whelan, 2001, Experiments in Color Texture Analysis, Pattern Recognition Letters, 22:1161-70.
  • Giorgio Giacinto, 2007. A Nearest Neighbor Approach to Relevance Feedback in Content based Image Retrieval, CIVR-2007, July 9-11, 2007, pp 456-463
  • Mei-Ling Shyu, Shu-Ching Chen, Chengcui Zhang, 2004, A unified framework for image database clustering and content based retrieval, MMDB-04, November 13, 2004, pp 19-27
  • Feng Jing, Bo Zhang, Fuzong Lin, Wei-Ying ma, 2001, A novel region based image retrieval method using relevance feedback, International conference on Multimedia information retrieval 2001, 28-31
  • James T. Miller, Ching-Chung Li. 1998 Adaptive Multi wavelets Initialization,. IEEE Transactions on signal processing, vol. 46, Issue 12, 282-291
  • A. W. M Smeulders, S. Santini, M. Worring, December 2000. Content Based Image Retrieval at the End of the Early Years, IEEE. Trans. PAMI, vol. 22, 1349-1380.
  • N G Kingsbury, 1998 The dual tree complex wavelet transform:. A new technique for shift invariance and directional filters, in Proc. 8th IEEE DSP workshop, Utah, Aug 9-12.
  • An Zhiyong, Zhao Feng, Image Retrieval based on Energy and Entropy of Multi wavelet Transform, 2009 International conference on Information Technology and Computer Science, . 544 -577.
  • K N Prakash, K Satyaprasad, 2012, M Band Dual tree complex wavelet transform for texture Image Indexing and Retrieval, International Journal of Advance in Engineering & Technology, Vol 4, Issue1, July 2012,. 661-671.
  • Pushpa Patil, Manesh Kokare, 2011,Semantic Image Retrieval Using Relevance Feedback, International Journal of Web & Semantic Technology, Vol 2, No. 4, October 2011, 139-148.
  • Karthik S, S Saha, Chaitra G, A 2013, New Relevance Feedback Based Approach for Efficient Image Retrieval, International Journal of Computer Application, Vol. 61, No. 14, January 2013,. 1-6.
  • Y. M. Latha, B. C. Jinaga and V. S. K Reddy, 2008, A Precise Content-Based Image Retrieval: Lifting Scheme ICGST-GVIP journal, vol. 8, issue 1, June 2008.
  • B. Jyoti, Y Madhavee Latha, and V. S. K Reddy, 2010, Relevance Feedback Content based Image retrieval using multiple features, IEEE conference on knowledge and data Engineering 2010.
  • Yu sun, Bir Bhanu, 2010, Image retrieval with feature selection and relevance feedback, Proceedings of IEEE, 17th International conference on Image Processing, September 26-29, 2010, Hong Kong.