Abstract
In this paper, we introduce a novel evolution-based segmentation algorithm by using the heat flow analogy, to gain practical advantage. The proposed algorithm consists of two parts. In the first part, we represent a particular heat conduction problem in the image domain to roughly segment the region of interest. Then we use geometric heat flow to complete the segmentation, by smoothing extracted boundaries and removing possible noise inside the prior segmented region. The proposed algorithm is compared with active contour models and is tested on synthetic and medical images. Experimental results indicate that our approach works well in noisy conditions without pre-processing. It can detect multiple objects simultaneously. It is also computationally more efficient and easier to control and implement in comparison to active contour models.
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Kass, M., Witkin, A., Terzopoulos, D.: Snakes: Active Contour models. IJCV, 321–331 (1987)
Xu, C., Prince, J.L.: Snakes, Shapes and Gradient Vector Flow. IEEE Transaction on Image Processing 7(3), 359–369 (1998)
Caselles, V., Catte, F., Coll, T., Dibos, F.: A Geometric Model for Active Contours. Numerische Mathematic 66, 1–31 (1993)
Malladi, R., Sethian, J.A., Vemuri, B.C.: Shape Modeling with Front Propagation: A Level Set Approach. IEEE Transaction on PAMI 17(2), 158–175 (1995)
Caselles, V., Kimmel, R., Sapiro, G.: Geodesic Active Contours. IJCV 22(1), 61–79 (1997)
Adalsteinsson, D., Sethian, J.: A Fast Level Set Method for Propagating Interfaces. J. Computational Physics 118(2), 269–277 (1995)
Sethian, J.: Level Set Methods and Fast Marching Methods. Cambridge Univ. press, New York (1999)
Weickert, J., Bart, M., Romeny, T.H., Viergever, M.A.: Efficient and Reliable Schemes for Nonlinear Diffusion Filtering. IEEE Transaction on Image Processing 7(3), 398–410 (1998)
Chan, T., Vese, L.: Active Contours without Edges. IEEE Transaction on Image Processing 10(2), 266–277 (2001)
Mumford, D., Shah, J.: Optimal Approximation by Piecewise Smooth Functions and Associated Variational Problems. Comm. Pure and Applied Math. 42, 577–685 (1989)
Adams, R., Bischof, L.: Seeded region growing. IEEE Trans. PAMI 16(6), 641–647 (1994)
Fung, P.W., Grebbin, G., Attikiouzel, Y.: Model-based region growing segmentation of textured images. In: ICASSP-90, vol. 4, pp. 2313–2316 (1990)
Perona, P., Malik, J.: Scale-Space and Edge Detection using Anisotropic Diffusion. IEEE Trans. PAMI 22(8), 629–639 (1990)
Kimia, B.B., Siddiqi, K.: Geometric Heat Equation and Nonlinear Diffusion of Shapes and Images. In: CVPR, pp. 113–120 (1994)
Direkoğlu, C., Nixon, M.S.: Low Level Moving-Feature Extraction via Heat Flow Analogy. In: Bebis, G., Boyle, R., Parvin, B., Koracin, D., Remagnino, P., Nefian, A., Meenakshisundaram, G., Pascucci, V., Zara, J., Molineros, J., Theisel, H., Malzbender, T. (eds.) ISVC 2006. LNCS, vol. 4291, pp. 243–252. Springer, Heidelberg (2006)
Acton, S.T., Bovik, A.C., Crawford, M.M.: Anisotropic diffusion pyramids for image segmentation. In: ICIP (1994)
Manay, S., Yezzi, A.: Anti-Geometric Diffusion for Adaptive Thresholding and Fast Segmentation. IEEE Transaction on Image Processing 12(11) (2003)
Holman, J.P.: Heat Transfer, 9th edn. McGraw-Hill, New York (2002)
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Direkoğlu, C., Nixon, M.S. (2007). Shape Extraction Via Heat Flow Analogy. In: Blanc-Talon, J., Philips, W., Popescu, D., Scheunders, P. (eds) Advanced Concepts for Intelligent Vision Systems. ACIVS 2007. Lecture Notes in Computer Science, vol 4678. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74607-2_50
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DOI: https://doi.org/10.1007/978-3-540-74607-2_50
Publisher Name: Springer, Berlin, Heidelberg
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