CFP last date
20 May 2024
Call for Paper
June Edition
IJCA solicits high quality original research papers for the upcoming June edition of the journal. The last date of research paper submission is 20 May 2024

Submit your paper
Know more
The week's pick
Responsive image
Enhancing Privacy Preservation: Multi-Attribute Protection with P-Sensitive K-Anonymity

Twinkle Patel Kiran Amin
Random Articles
Reseach Article

An Effective Image Retrieval System using Region and Contour based Features

Published on April 2012 by Chandan Singh, Pooja
journal_cover_thumbnail

International Conference on Recent Advances and Future Trends in Information Technology (iRAFIT 2012)
Foundation of Computer Science USA
IRAFIT - Number 2
April 2012
Authors: Chandan Singh, Pooja
62238133-00b1-454f-b8cd-e5935775be71

Chandan Singh, Pooja . An Effective Image Retrieval System using Region and Contour based Features. International Conference on Recent Advances and Future Trends in Information Technology (iRAFIT 2012). IRAFIT, 2 (April 2012), 7-12.

@article{
author = { Chandan Singh, Pooja },
title = { An Effective Image Retrieval System using Region and Contour based Features },
journal = { International Conference on Recent Advances and Future Trends in Information Technology (iRAFIT 2012) },
issue_date = { April 2012 },
volume = { IRAFIT },
number = { 2 },
month = { April },
year = { 2012 },
issn = 0975-8887,
pages = { 7-12 },
numpages = 6,
url = { /proceedings/irafit/number2/5854-1010/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 International Conference on Recent Advances and Future Trends in Information Technology (iRAFIT 2012)
%A Chandan Singh
%A Pooja
%T An Effective Image Retrieval System using Region and Contour based Features
%J International Conference on Recent Advances and Future Trends in Information Technology (iRAFIT 2012)
%@ 0975-8887
%V IRAFIT
%N 2
%P 7-12
%D 2012
%I International Journal of Computer Applications
Abstract

In this paper, a hybrid approach is proposed for improving the image retrieval accuracy. In the hybrid approach both local and global features of images are combined, which represent the entire aspects of images. Local features are extracted using Fourier descriptors and global features are extracted by means of angular radial transform. The results of combining both these descriptors demonstrate that the proposed solution provides significant improvement in image retrieval accuracy as compared to using global and local features autonomously. Besides, it also outperforms existing recent hybrid approaches to image retrieval.

References
  1. Veltkamp, R., Burkhardt, H., Kriegel, H.-P., 2008. State-of-the-Art in content-based image and video retrieval, Kluwer Academic Publishers, New York.
  2. Long, F., Zhang, H.J., Feng, D.D., 2003. Fundamentals of content-based image retrieval, in: D.D. Feng, W.C. Siu, H.J. Zhang (Eds.), Multimedia Information Retrieval and Management—Technological Fundamentals and Applications, Springer 1–27.
  3. Kim, W.-Y., Kim, Y.-S., 2000. A region based shape descriptor using Zernike moments, Sig Process: Image Commun. (16) 95–102.
  4. Zhang, D., Lu G., (2003) A comparative study of curvature scale space and Fourier descriptors for shape based image retrieval, J. Vis. Commun. Image R. (14) 41-60.
  5. Mokhtarian, F., Abbasi, F., Kittler, J., 1997. Efficient and robust retrieval by shape content through curvature scale space, Int. workshop on Image Databases and Multi-Media Search 51–58.
  6. Attalla, E., Siy, P., 2005. Robust shape similarity retrieval based on contour segmentation polygonal multiresolution and elastic matching, Pattern Recoginit. (38) 2229–2241.
  7. Freeman, H., 1961. On the encoding of arbitrary geometric configurations. IRE Trans. Electron. Comput. (10) 260–268.
  8. Bober, M., 2001 MPEG-7 visual shape descriptors, IEEE Trans. Circuits Syst. Video Technol. (11) 716-719.
  9. Hu, M.-K., 1962. Visual pattern recognition by moment invariants, IRE Trans. Inf. Theory 8 (2) 179–187.
  10. Zhang, D., Lu, G., 2002. Shape-based image retrieval using generic Fourier descriptor, Signal Process.: Image Commun. 17 (10) 825–848.
  11. Wei, C.H., Li, Y., Chau, W.-Y., and Li, C.-T., 2008. Trademark image retrieval using synthetic features for describing global shape and interior structure, Pattern Recognit. (42) 386–394.
  12. Qi, H., Li, K., Shen, Y., Qu, W., 2010. An effective solution for trademark image retrieval by combining shape description and feature matching, Pattern Recognit. (43) 2017–2027.
  13. D. Zhang, G. Lu, Evaluation of MPEG-7 shape descriptors against other shape descriptors, Multimed. Syst. 9 (2003) 15-30.
  14. A. Amanatiadis, V.G. Kaburlasos, A. Gasteratos, S.E. Papadakis, Evaluation of shape descriptors for shape based image retrieval, IET Image Process. 5 (5) (2011) 493-499.
  15. Singh, C., Pooja, 2011. Improving image retrieval using combined features of Hough transform and Zernike moments, Opt. Laser Eng. (49) 1386-1396.
  16. Singh, C., Walia, E., 2011. Algorithms for fast computation of Zernike moments and their numerical stability, Image Vis. Comput. 29 (4) 251-259.
Index Terms

Computer Science
Information Sciences

Keywords

Angular Radial Transform Fourier Descriptor Zernike Moments