- 1. T. Batard, C. Saint-Jean, M. Berthier, A Metric Approach to nD Images Edge Detection
 with Clifford Algebras, J. Math. Imaging Vis. 33(2009), 296-312. 
- 2. F. Benmansour, L. D. Cohen, Fast Object Segmentation by Growing Minimal Paths from
 a Single Point on 2D or 3D Images, J. Math. Imaging Vis. 33(2009), 209-221. 
- 3. P. Bose, A. Maheshwari, C. Shu, S. Wuhrer, A Survey of Geodesic Paths on 3D Surfaces,
 Computational Geometry, 44(2011), 486-498. 
- 4. A. Cumani, Edge Detection in Multispectral Images, Graphical Models and Image Processing, 53, 1991, 40-51.
 
- 5. A. Gooya, T. Dohi, I. Sakuma, H. Liao, R-PLUS: A Riemannian Anisotropic Edge
 Detection Scheme for Vascular Segmentation, Medical Image Computing and ComputerAssisted Intervention (MICCAI, 2008), 262-269. 
- 6. R. Kimmel, N. Sochen, R. Malladi, From high energy physics to low level vision, ScaleSpace Theory in Computer Vision, 1997.
 
- 7. U. Kothe, Edge and Junction Detection with an Improved Structure Tensor, Pattern
 Recognition Proceeding, 2003, 25-32. 
- 8. D. Marr, Vision, MIT Press, 2010.
 
- 9. E, Peyghan, E. Sharahi, A. Baghban, Adams-Moulton Method approach to geodesic paths
 on 2D surfaces, MACO. 1(2020), 81-93. 
- 10. G. Peyr, M. Pchaud, R. Keriven, L. D. Cohen, Geodesic Methods in Computer Vision and
 Graphics, Foundations and Trends in Computer Graphics and Vision, Now Publishers, 5, 2010, 197-397. 
- 11. D. Phillips, Image processing in C, Prentice Hall, 1994.
 
- 12. M. M. Postnikov, Geometry VI: Riemannian Geometry, Springer-Verlag, 2001.
 
- 13. G. Sapiro, Geometric Partial Differential Equations and Image Analysis, Cambridge
 University Press, 2006. 
- 14. C. Scheffer, J. Vahrenhold, Approximating geodesic distances on 2-manifolds in R2
 , Computational Geometry. 47(2014), 125-140. 
- 15. Z. Zhang, E. Klassen, A. Srivastava, P. Turaga, R. Chellappa Blurring-Invariant Riemannian Metrics for Comparing Signals and Images, IEEE International Conference on
 Computer Vision, 2011. 
- 16. D. Zosso, X, Bresson, JP. Thiran, Geodesic active fields-a geometric framework for image
 registration, IEEE Trans Image Process, 20(2011), 1300-1312 
  			 
			 |