Skip to main content
Log in

Geodesic Distance and Curves Through Isotropic and Anisotropic Heat Equations on Images and Surfaces

  • Published:
Journal of Mathematical Imaging and Vision Aims and scope Submit manuscript

Abstract

This paper proposes a method to extract geodesic distance and geodesic curves using heat diffusion. The method is based on Varadhan’s formula that helps to obtain a numerical approximation of geodesic distance according to metrics based on different heat flows. The heat equation can be utilized by regarding an image or a surface as a medium for heat diffusion and letting the user set at least one source point in the domain. Both isotropic and anisotropic diffusions are considered here to obtain geodesics according to their respective metrics. (1) In the part of the paper where we deal with the isotropic case, we use gray-level intensity to compute the conductivity, i.e., those pixels with gray-levels similar to the source point would have higher conductivity. The model of Perona and Malik, which inhibits heat from diffusing out of homogeneous regions, is also used for geodesic computations in this paper. The two methods are combined and used for more complicated cases. We can also use the norm of the gradient of an image as the feature in the Perona and Malik model to make the heat diffuse along boundaries and edges. (2) For the anisotropic case, we use different eigenvectors and eigenvalues to compose the diffusion tensors to concentrate heat flow along chosen directions. Furthermore, to automate the process of extracting geodesic lines, we propose two automatic methods: a new voting method and a key point method, which are both especially designed for the heat-based method. Our algorithms are tested on synthetic and real images as well as on a mesh. The results are very promising and demonstrate the robustness of the algorithms.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14
Fig. 15
Fig. 16
Fig. 17
Fig. 18
Fig. 19
Fig. 20

Similar content being viewed by others

References

  1. Alliez, P., Cohen-Steiner, D., Devillers, O., Lévy, B., Desbrun, M.: Anisotropic polygonal remeshing. In: ACM Transactions on Graphics (TOG), vol. 22, pp. 485–493. ACM, New York (2003)

  2. Benmansour, F., Cohen, L.D.: Fast object segmentation by growing minimal paths from a single point on 2D or 3D images. J. Math. Imaging Vis. 33(2), 209–221 (2009)

    Article  MathSciNet  Google Scholar 

  3. Benmansour, F., Cohen, L.D.: Tubular anisotropy segmentation. Scale Space and Variational Methods in Computer Vision. Springer, Berlin (2009)

    Google Scholar 

  4. Cohen, L.D., Kimmel, R.: Global minimum for active contour models: a minimal path approach. Int. J. Comput. Vis. 24(1), 57–78 (1997)

    Article  Google Scholar 

  5. Cohen-Steiner, D., Morvan, J.-M.: Restricted delaunay triangulations and normal cycle. In: Proceedings of the Nineteenth Annual Symposium on Computational Geometry, pp. 312–321. ACM, New York (2003)

  6. Constantinescu, R., Costanzino, N., Mazzucato, A.L., Nistor, V.: Approximate Solutions to Second Order Parabolic Equations I: Analytic Estimates. arXiv:0910.1562 (2009)

  7. Courant, R., Friedrichs, K., Lewy, H.: On the partial difference equations of mathematical physics. IBM J. Res. Dev. 11(2), 215–234 (1967)

    Article  MathSciNet  MATH  Google Scholar 

  8. Crane, K., Weischedel, C., Wardetzky, M.: Geodesics in heat: a new approach to computing distance based on heat flow. ACM Trans. Graphics 32(5), 152 (2013)

    Article  Google Scholar 

  9. Dijkstra, E.W.: A note on two problems in connexion with graphs. Numer. Math. 1(1), 269–271 (1959)

    Article  MathSciNet  MATH  Google Scholar 

  10. Fehrenbach, J., Mirebeau, J.-M.: Sparse non-negative stencils for anisotropic diffusion. J. Math. Imaging Vis. 49(1), 123–147 (2014)

    Article  MathSciNet  MATH  Google Scholar 

  11. Frangi, A.F., Niessen, W.J., Vincken, K.L., Viergever, M.A.: Multiscale vessel enhancement filtering. In: Medical Image Computing and Computer-Assisted Intervention, MICCAI’98, pp. 130–137. Springer, New York (1998)

  12. Hu, J., Razdan, A., Femiani, J.C., Cui, M., Wonka, Peter: Road network extraction and intersection detection from aerial images by tracking road footprints. IEEE Trans. Geosci. Remote Sens. 45(12), 4144–4157 (2007)

    Article  Google Scholar 

  13. Jbabdi, S., Bellec, P., Toro, R., Daunizeau, J., Pélégrini-Issac, M., Benali, H.: Accurate anisotropic fast marching for diffusion-based geodesic tractography. J. Biomed. Imaging 2008, 2 (2008)

    Google Scholar 

  14. Sun, J., Ovsjanikov, M., Guibas, L.: A concise and provably informative multi-scale signature based on heat diffusion. Comput. Graphics Forum 28(5), 1383–1392 (2009)

    Article  Google Scholar 

  15. Weickert, J.: Anisotropic Diffusion in Image Processing. Teubner, Stuttgart (1998)

    MATH  Google Scholar 

  16. Kaul, V., Yezzi, A., Tsai, Y.: Detecting curves with unknown endpoints and arbitrary topology using minimal paths. IEEE Trans. Pattern Anal. Mach. Intell. 34(10), 1952–1965 (2012)

    Article  Google Scholar 

  17. Sermesant, M., Clatz, O., Peyrat, J.M., Delingette H., Konukoglu, E., Ayache, N.: A recursive anisotropic fast marching approach to reaction diffusion equation: application to tumor growth modeling. In: Information Processing in Medical Imaging. Springer, Berlin (2007)

  18. Köthe, U.: Edge and junction detection with an improved structure tensor. In: Pattern Recognition, pp. 25–32. Springer, New York (2003)

  19. Law, M.W.K., Chung, A.C.S.: Three dimensional curvilinear structure detection using optimally oriented flux. In: European Conference on Computer Vision, ECCV 2008, pp. 368–382. Springer, Berlin (2008)

  20. Mirebeau, J.-M.: Anisotropic fast-marching on cartesian grids using lattice basis reduction. SIAM J. Numer. Anal. 52(4), 1573–1599 (2014)

    Article  MathSciNet  MATH  Google Scholar 

  21. Mirebeau, J-M, Fehrenbach, J, Risser, L., Tobji, S.: Anisotropic diffusion in ITK. arXiv:1503.00992 (2015)

  22. Pardoux, E.: Stochastic partial differential equations and filtering of diffusion processes. Stochastics 3(1–4), 127–167 (1980)

    Article  MathSciNet  MATH  Google Scholar 

  23. Perona, P., Malik, J.: Scale-space and edge detection using anisotropic diffusion. IEEE Trans. Pattern Anal. Mach. Intell. 12(7), 629–639 (1990)

    Article  Google Scholar 

  24. Peyré, G., Péchaud, M., Keriven, R., Cohen, L.D.: Geodesic methods in computer vision and graphics. Found. Trends Comput. Graphics Vis. 5(3–4), 197–397 (2010)

  25. Pinkall, U., Polthier, K.: Computing discrete minimal surfaces and their conjugates. Exp. Math. 2(1), 15–36 (1993)

    Article  MathSciNet  MATH  Google Scholar 

  26. Raviv, D., Kimmel, R.: Affine invariant geometry for non-rigid shapes. Int. J. Comput. Vis. 111(1), 1–11 (2015)

  27. Reuter, Mn, Biasotti, S., Giorgi, D., Patanè, G., Spagnuolo, M.: Discrete Laplace–Beltrami operators for shape analysis and segmentation. Comput. Graphics 33(3), 381–390 (2009)

    Article  Google Scholar 

  28. Rouchdy, Y., Cohen, L.D.: Image segmentation by geodesic voting. application to the extraction of tree structures from confocal microscope images. In: 19th International Conference on Pattern Recognition, ICPR 2008., pp. 1–5. IEEE (2008)

  29. Rouchdy, Y., Cohen, L.D.: A geodesic voting method for the segmentation of tubular tree and centerlines. In: 2011 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, pp. 979–983. IEEE (2011)

  30. Rouchdy, Y., Cohen, L.D.: Geodesic voting for the automatic extraction of tree structures. Comput. Vis. Image Underst. 117(10), 1453–1467 (2013)

    Article  Google Scholar 

  31. Sethian, J.A.: A fast marching level set method for monotonically advancing fronts. Proc. Natl. Acad. Sci. USA 93(4), 1591–1595 (1996)

    Article  MathSciNet  MATH  Google Scholar 

  32. Sethian, J.A., Vladimirsky, A.: Fast methods for the eikonal and related Hamilton–Jacobi equations on unstructured meshes. Proc. Natl. Acad. Sci. USA 97(11), 5699–5703 (2000)

    Article  MathSciNet  MATH  Google Scholar 

  33. Varadhan, S.R.S.: On the behavior of the fundamental solution of the heat equation with variable coefficients. Commun. Pure Appl. Math. 20(2), 431–455 (1967)

    Article  MathSciNet  MATH  Google Scholar 

  34. Taylor, T.J.S.: Off diagonal asymptotics of hypoelliptic diffusion equations and singular Riemannian geometry. Pac. J. Math. 136(2), 379–399 (1989)

    Article  MathSciNet  MATH  Google Scholar 

  35. Unsworth, J., Duarte, F.J.: Heat diffusion in a solid sphere and Fourier theory: an elementary practical example. Am. J. Phys. 47(11), 981–983 (1979)

    Article  Google Scholar 

  36. Vassilevich, D.V.: Heat Kernel expansion: user’s manual. Phys. Rep. 388(5), 279–360 (2003)

    Article  MathSciNet  MATH  Google Scholar 

  37. Weickert, J.: Coherence-enhancing diffusion filtering. Int. J. Comput. Vis. 31(2–3), 111–127 (1999)

    Article  Google Scholar 

  38. Witkin, A.P.: Scale-space filtering: a new approach to multi-scale description. In: IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP’84., vol. 9, pp. 150–153. IEEE (1984)

Download references

Acknowledgments

We would like to thank the anonymous reviewers, as well as Aristide-Oswald Bartet, for their useful comments that allowed us to improve this paper. Our Special thanks to Dr. Vivek Kaul and Prof.Anthony Yezzi who made a complete reading of our paper in order to check for correct English and helped for this revision. Also, many thanks to Jean-Marie Mirebeau, Dario Prandi, and Gabriel Peyré for fruitful discussions.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Fang Yang.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Yang, F., Cohen, L.D. Geodesic Distance and Curves Through Isotropic and Anisotropic Heat Equations on Images and Surfaces. J Math Imaging Vis 55, 210–228 (2016). https://doi.org/10.1007/s10851-015-0621-9

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10851-015-0621-9

Keywords

Navigation