Table of Contents Author Guidelines Submit a Manuscript
Mathematical Problems in Engineering
Volume 2013 (2013), Article ID 452604, 12 pages
http://dx.doi.org/10.1155/2013/452604
Research Article

Robust Image Matching Algorithm Using SIFT on Multiple Layered Strategies

1School of Energy Science and Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China
2School of Mechanical Engineering, The University of Adelaide, Adelaide 5005, Australia

Received 4 June 2013; Revised 18 October 2013; Accepted 1 November 2013

Academic Editor: Gradimir Milovanović

Copyright © 2013 Yong Chen et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. Y. Zhou, S. T. Zhou, Z. Y. Zhong, and H. G. Li, “A de-illumination scheme for face recognition based on fast decomposition and detail feature fusion,” Optics Express, vol. 21, no. 9, pp. 11294–11308, 2013. View at Publisher · View at Google Scholar
  2. D. G. Lowe, “Distinctive image features from scale-invariant keypoints,” International Journal of Computer Vision, vol. 60, no. 2, pp. 91–110, 2004. View at Publisher · View at Google Scholar · View at Scopus
  3. A. E. Abdel-Hakim and A. A. Farag, “CSIFT: a SIFT descriptor with color invariant characteristics,” in Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR '06), pp. 1978–1983, New York, NY, USA, June 2006. View at Publisher · View at Google Scholar · View at Scopus
  4. K. Mikolajczyk and C. Schmid, “A performance evaluation of local descriptors,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 27, no. 10, pp. 1615–1630, 2005. View at Publisher · View at Google Scholar · View at Scopus
  5. Y. L. Wang, J. X. Shen, W. H. Liao, and L. Zhou, “Automatic fundus images mosaic based on SIFT feature,” Journal of Image and Graphics, vol. 16, no. 4, pp. 2747–2751, 2010. View at Google Scholar
  6. L. J. Li and X. Long, “LSIFT—an improved SIFT algorithm with a new matching method,” in Proceedings of the International Conference on Computer Application and System Modeling (ICCASM '10), pp. V4-643–V4-646, Taiyuang, China, October 2010. View at Publisher · View at Google Scholar · View at Scopus
  7. J. Liu, G. H. Zhang, and L. L. Huang, “Image registration approach based on improved SIFT,” Journal of Beijing University of Aeronautics and Astronautics, vol. 36, no. 9, pp. 1121–1124, 2010. View at Google Scholar · View at Scopus
  8. S. Belongie, J. Malik, and J. Puzicha, “Shape matching and object recognition using shape contexts,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 24, no. 4, pp. 509–522, 2002. View at Publisher · View at Google Scholar · View at Scopus
  9. Y. Bastanlar, A. Temizel, and Y. Yardimci, “Improved SIFT matching for image pairs with scale difference,” Electronics Letters, vol. 46, no. 5, pp. 346–348, 2010. View at Publisher · View at Google Scholar · View at Scopus
  10. Z. L. Song, S. Li, and T. F. George, “Remote sensing image registration approach based on a retrofitted sift algorithm and lissajous-curve trajectories,” Optics Express, vol. 18, no. 2, pp. 513–522, 2010. View at Publisher · View at Google Scholar · View at Scopus
  11. Q. L. Li, G. Y. Wang, J. G. Liu, and S. Chen, “Robust scale-invariant feature matching for remote sensing image registration,” IEEE Geoscience and Remote Sensing Letters, vol. 6, no. 2, pp. 287–291, 2009. View at Publisher · View at Google Scholar · View at Scopus
  12. Z. Yi, C. Zhiguo, and X. Yang, “Multi-spectral remote image registration based on SIFT,” Electronics Letters, vol. 44, no. 2, pp. 107–108, 2008. View at Publisher · View at Google Scholar · View at Scopus
  13. C. Schmid, R. Mohr, and C. Bauckhage, “Evaluation of interest point detectors,” International Journal of Computer Vision, vol. 37, no. 2, pp. 151–172, 2000. View at Publisher · View at Google Scholar · View at Zentralblatt MATH · View at Scopus