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All issues Volume 32 (2020) ITM Web Conf., 32 (2020) 03043 References
Open Access
Issue
ITM Web Conf.
Volume 32, 2020
International Conference on Automation, Computing and Communication 2020 (ICACC-2020)
Article Number 03043
Number of page(s) 5
Section Computing
DOI https://doi.org/10.1051/itmconf/20203203043
Published online 29 July 2020
  1. David G. Lowe. Object recognition from local scale-invariant features, In Proceedings of the Seventh IEEE International Conference on Computer Vision, Corfu, Greece, 1999. [Google Scholar]
  2. Yu-Dae Ban, Jaeyeon Lee, Dae Hwan Hwang, Yun-Koo Chung. Face Image registration methods using Normalized Cross Correlation International Conference on Control. Automation and Systems, 2008, pp.2408-2411. [Google Scholar]
  3. David G. Lowe. Distinctive image features from scale-invariant key-points. International Journal of Computer Vision, 2004, (60), pp. 91-110. [Google Scholar]
  4. Yan Ke and R. Sukthankar. PCA-SIFT: a more distinctive representation for local image descriptors. In Proceedings IEEE Computer Society Conference on Computer Vision and Pattern Recognition. 2004 July, 2(2), pp. 506-513. [CrossRef] [Google Scholar]
  5. Danijela Ristic-Durrant Faraj Alhwarin, Chao Wang, and Axel Grser. Improved sift features matching for object recognition. BCS International Academic Conference 2008 Visions of Computer Science. 2008, pp. 179-190. [Google Scholar]
  6. Luo Juan and Oubong Gwon. A Comparison of SIFT, PCA-SIFT, and SURF. International Journal of Image Processing (IJIP). 2009, 3(4), pp. 143-152. [Google Scholar]
  7. Jignesh N Sarvaiya, Dr. Suprava Patnaik, Salman Bombaywala. Image registration using Log polar transform and phase correlation. IEEE Region 10 Conference TENCON. 2009, pp. 1-5. [Google Scholar]
  8. Hast, Anders. Robust and Invariant Phase Based Local Feature Matching. 22nd International Conference on Pattern Recognition (ICPR). 2014, ISSN: 1051-4651, pp. 809-814. [Google Scholar]
  9. Wolberg G., Zokai S, Robust image registration using log-polar transform, In Proceeding International Conference on Image Processing, 2000 September, pp. 493-496. [Google Scholar]
  10. Y. Keller, A. Averbuch, M. Israeli. Pseudo polar-based estimation of large translations, rotations, and scalings in images. IEEE Trans. on Image processing. 2005, pp. 12-22. [Google Scholar]
  11. H. Liu, B. Guo, and Z. Feng. Pseudo-log-polar Fourier transforms for image registration. IEEE Transaction Signal Processing Letters. 2006 January, 13(1), pp. 1720. [Google Scholar]
  12. R. Matungka, Y.F. Zheng, and R.L. Ewing. 2D invariant object recognition using log-polar transform. In Proc. World Congress on Intelligent Control and Automation, 2008 January, pp. 223-228. [Google Scholar]
  13. A.N. Myrna, M.G. Venkateshmurthy, and C.G. Patil. Detection of region duplication forgery in digital images using wavelets and log-polar mapping. In Proc. Intl. Conf. Computational Intelligence and Multimedia Applications, 2007 December, (3), pp. 371-377. [Google Scholar]
  14. Xiaoxin Guo, Zhiwen Xu, Yinan Lu, and Yunjie Pang. An Application of Fourier-Mellin Transform in Image Registration. Proceedings of The Fifth International Conference on Computer and Information Technology, 2005, pp.619-623. [Google Scholar]
  15. B. Srinivasa Reddy and B.N. Chatterji. An FFT-Based Technique for Translation, Rotation, and Scale-Invariant Image Registration. IEEE Trans. on Image Processing. 1996, (5), pp.1266-1271. [Google Scholar]
  16. Xiaoxin Guo, Zhiwen Xu, Yinan Lu, and Yunjie Pang. An Application of Fourier-Mellin Transform in Image Registration. Proceedings of The Fifth International Conference on Computer and InformationTechnology, 2005, pp.619-623. [Google Scholar]
  17. Y. Keller, A. Averbuch, M. Israeli. Pseudo polar-based estimation of large translations, rotations, and scalings in the image. IEEE transaction on Image processing. 2005, pp. 12-22. [Google Scholar]

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