# American Institute of Mathematical Sciences

August  2014, 8(3): 845-863. doi: 10.3934/ipi.2014.8.845

## Active arcs and contours

 1 Department of Mathematics, University of California, Irvine, Irvine, CA 92697, United States

Received  September 2012 Revised  November 2013 Published  August 2014

The level set method [33] is a commonly used framework for image segmentation algorithms. For edge detection and segmentation models, the standard level set method provides a flexible curve representation and implementation. However, one drawback has been in the types of curves that can be represented in this standard method. In the classical level set method, the curve must enclose an open set (i.e. loops or contours without endpoints). Thus the classical framework is limited to locating edge sets without endpoints. Using the curve representation from [37,36], we construct a segmentation and edge detection method which can locate arcs (i.e. curves with free endpoints) as well as standard contours. Within this new framework, the variational segmentation model presented here is able to detect general edge structures and linear objects. This energy is composed of two terms, an edge set regularizer and an edge attractor. Our variational model is related to the Mumford and Shah model [29] for joint segmentation and restoration in terms of an asymptotic limit, and in addition, is both general and flexible in terms of its uses and its applications. Numerical results are given on images with a variety of edge structures.
Citation: Hayden Schaeffer. Active arcs and contours. Inverse Problems & Imaging, 2014, 8 (3) : 845-863. doi: 10.3934/ipi.2014.8.845
##### References:
 [1] L. Alvarez, L. Baumela, P. Márquez-Neila and P. Henríquez, A Real Time Morphological Snakes Algorithm,, Image Processing On Line, (2012). Google Scholar [2] L. Ambrosio and V. M. Tortorelli, Approximation of functional depending on jumps by elliptic functional via $\Gamma$-convergence,, Communications on Pure and Applied Mathematics, 43 (1990), 999. doi: 10.1002/cpa.3160430805. Google Scholar [3] D. Bao, S.-S. Chern and Z.Shen, An Introduction to Riemann-Finsler Geometry, {Vol.} 200,, Springer, (2000). doi: 10.1007/978-1-4612-1268-3. Google Scholar [4] L. Bar and G. Sapiro, Generalized Newton-Type methods for energy formulations in image processing,, SIAM Journal on Imaging Sciences, 2 (2009), 508. doi: 10.1137/080722436. Google Scholar [5] S. Basu, D. P. Mukherjee and S. T. Acton, Implicit evolution of open ended curves,, In Image Processing, 1 (2007). doi: 10.1109/ICIP.2007.4378941. Google Scholar [6] V. Caselles, R. Kimmel and G. Sapiro, Geodesic active contours,, International Journal of Computer Vision, 22 (1995), 694. doi: 10.1109/ICCV.1995.466871. Google Scholar [7] T. F. Chan, B. Y. Sandberg and L. A. Vese, Active contours without edges for vector-valued images,, Journal of Visual Communication and Image Representation, 11 (2000), 130. doi: 10.1006/jvci.1999.0442. Google Scholar [8] T. F. Chan and L. A. Vese, Active contours without edges,, IEEE Transactions on Image Processing, 10 (2001), 266. doi: 10.1109/83.902291. Google Scholar [9] G. Chung and L. A. Vese, Image segmentation using a multilayer level-set approach,, Computing and Visualization in Science, 12 (2009), 267. doi: 10.1007/s00791-008-0113-1. Google Scholar [10] L. D. Cohen and R. Kimmel, Global minimum for active contour models: A minimal path approach,, International Journal of Computer Vision, 24 (1997), 57. Google Scholar [11] M. G. Crandall, L. C. Evans and R. F. Gariepy, Optimal Lipschitz extensions and the infinity Laplacian,, Calculus of Variations and Partial Differential Equations, 13 (2001), 123. Google Scholar [12] G. Dal Maso, J. M. Morel and S. Solimini, A variational method in image segmentation: Existence and approximation results,, Acta Mathematica, 168 (1992), 89. doi: 10.1007/BF02392977. Google Scholar [13] L. C. Evans and R. F. Gariepy, Measure Theory and Fine Properties of Functions,, CRC Press, (1992). Google Scholar [14] L. C. Evans and Y. Yu, Various properties of solutions of the Infinity-Laplacian equation,, Communications in Partial Differential Equations, 30 (2005), 1401. doi: 10.1080/03605300500258956. Google Scholar [15] E. De Giorgi, M. Carriero and A. Leaci, Existence theorem for a minimum problem with free discontinuity set,, Archive for Rational Mechanics and Analysis, 108 (1989), 195. doi: 10.1007/BF01052971. Google Scholar [16] M. Jung, G. Chung, G. Sundaramoorthi, L. A. Vese and A. L. Yuille, Sobolev gradients and joint variational image segmentation, denoising, and deblurring,, IS&T/SPIE Electronic Imaging, 7246 (2009). doi: 10.1117/12.806067. Google Scholar [17] M. Kass, A. Witkin and D. Terzopoulos, Snakes: Active contour models,, International Journal of Computer Vision, 1 (1988), 321. doi: 10.1007/BF00133570. Google Scholar [18] M. S. Keegan, B. Sandberg and T. F. Chan, A multiphase logic framework for multichannel image segmentation,, Inverse Problems and Imaging, 6 (2012), 95. doi: 10.3934/ipi.2012.6.95. Google Scholar [19] S. Kichenassamy, A. Kumar, P. Olver, A. Tannenbaum and A. Yezzi, Gradient flows and geometric active contour models,, In Computer Vision, (1995), 810. doi: 10.1109/ICCV.1995.466855. Google Scholar [20] R. Kimmel and A. M. Bruckstein, Regularized Laplacian zero crossings as optimal edge integrators,, International Journal of Computer Vision, 53 (2001), 225. Google Scholar [21] C. Lacoste, X. Descombes and J. Zerubia, Unsupervised line network extraction in remote sensing using a polyline process,, Pattern Recognition, 43 (2010), 1631. doi: 10.1016/j.patcog.2009.11.003. Google Scholar [22] C. Larsen, C. Richardson and M. Sarkis, A Level Set Method for the Mumford -Shah Functional and Fracture,, Inst. Nacional de Matemática Pura e Aplicada, (2008). Google Scholar [23] S. Leung and H. Zhao, A grid based particle method for evolution of open curves and surfaces,, Journal of Computational Physics, 228 (2009), 7706. doi: 10.1016/j.jcp.2009.07.017. Google Scholar [24] W. H. Liao, L. Vese, S. C. Huang, M. Bergsneider and S. Osher, Computational anatomy and implicit object representation: A level set approach,, In Biomedical Image Registration, 2717 (2003), 40. doi: 10.1007/978-3-540-39701-4_5. Google Scholar [25] G. Lu and P. Wang, Inhomogeneous infinity Laplace equation,, Advances in Mathematics, 217 (2008), 1838. doi: 10.1016/j.aim.2007.11.020. Google Scholar [26] J. Melonakos, E. Pichon, S. Angenent and A. Tannenbaum, Finsler active contours,, Pattern Analysis and Machine Intelligence, 30 (2008), 412. doi: 10.1109/TPAMI.2007.70713. Google Scholar [27] J. M. Morel and S. Solimini, Segmentation of images by variational methods: A constructive approach,, Revista Matemática de la Universidad Complutense de Madrid, 1 (1988), 169. Google Scholar [28] J. M. Morel and S. Solimini, Segmentation d'images par méthode variationnelle: Une preuve constructive d'existence,, Comptes rendus de l'Académie des sciences. Série 1, 308 (1989), 465. Google Scholar [29] D. Mumford and J. Shah, Optimal approximations by piecewise smooth functions and associated variational problems,, Communications on Pure and Applied Mathematics, 42 (1989), 577. doi: 10.1002/cpa.3160420503. Google Scholar [30] J. W. Neuberger, Sobolev Gradients and Differential Equations,, Lecture Notes in Mathematics, (2010). doi: 10.1007/978-3-642-04041-2. Google Scholar [31] C. Niemann, A. S. Bondarenko, C. G. Constantin, E. T. Everson, K. A. Flippo, S. A. Gaillard, R. P. Johnson, S. A. Letzring, D. S. Montgomery, L. A. Morton, D. B. Schaeffer, T. Shimada and D. Winske, Collisionless shocks in a large magnetized laser-plasma plume,, Plasma Science, 39 (2011), 2406. doi: 10.1109/TPS.2011.2162007. Google Scholar [32] A. M. Oberman, A convergent difference scheme for the infinity laplacian: Construction of absolutely minimizing Lipschitz extensions,, Mathematics of Computation, 74 (2005), 1217. doi: 10.1090/S0025-5718-04-01688-6. Google Scholar [33] S. Osher and J. A. Sethian, Fronts propagating with curvature-dependent speed: Algorithms based on Hamilton-Jacobi formulations,, Journal of Computational Physics, 79 (1988), 12. doi: 10.1016/0021-9991(88)90002-2. Google Scholar [34] R. J. Renka, A simple explanation of the Sobolev gradient method,, Unpublished, (2006). Google Scholar [35] W. B. Richardson, Sobolev gradient preconditioning for image-processing PDEs,, Communications in Numerical Methods in Engineering, 24 (2008), 493. doi: 10.1002/cnm.951. Google Scholar [36] H. Schaeffer and L. Vese, Active contours with free endpoints,, Journal of Mathematical Imaging and Vision, 49 (2014), 20. doi: 10.1007/s10851-013-0437-4. Google Scholar [37] P. Smereka, Spiral crystal growth,, Physica D: Nonlinear Phenomena, 138 (2000), 282. doi: 10.1016/S0167-2789(99)00216-X. Google Scholar [38] G. Sundaramoorthi, A. Yezzi and A. C. Mennucci, Sobolev active contours,, Lecture Notes in Computer Science, 3752 (2005), 109. doi: 10.1007/11567646_10. Google Scholar [39] A. Tsai, A. Yezzi Jr and A. S. Willsky, Curve evolution implementation of the Mumford-Shah functional for image segmentation, denoising, interpolation, and magnification,, Image Processing, 10 (2001), 1169. doi: 10.1109/83.935033. Google Scholar [40] L. A. Vese and T. F. Chan, A multiphase level set framework for image segmentation using the Mumford and Shah model,, International Journal of Computer Vision, 50 (2002), 271. Google Scholar [41] C. Zach, L. Shan and M. Niethammer, Globally optimal Finsler active contours,, In Pattern Recognition, 5748 (2009), 552. doi: 10.1007/978-3-642-03798-6_56. Google Scholar

show all references

##### References:
 [1] L. Alvarez, L. Baumela, P. Márquez-Neila and P. Henríquez, A Real Time Morphological Snakes Algorithm,, Image Processing On Line, (2012). Google Scholar [2] L. Ambrosio and V. M. Tortorelli, Approximation of functional depending on jumps by elliptic functional via $\Gamma$-convergence,, Communications on Pure and Applied Mathematics, 43 (1990), 999. doi: 10.1002/cpa.3160430805. Google Scholar [3] D. Bao, S.-S. Chern and Z.Shen, An Introduction to Riemann-Finsler Geometry, {Vol.} 200,, Springer, (2000). doi: 10.1007/978-1-4612-1268-3. Google Scholar [4] L. Bar and G. Sapiro, Generalized Newton-Type methods for energy formulations in image processing,, SIAM Journal on Imaging Sciences, 2 (2009), 508. doi: 10.1137/080722436. Google Scholar [5] S. Basu, D. P. Mukherjee and S. T. Acton, Implicit evolution of open ended curves,, In Image Processing, 1 (2007). doi: 10.1109/ICIP.2007.4378941. Google Scholar [6] V. Caselles, R. Kimmel and G. Sapiro, Geodesic active contours,, International Journal of Computer Vision, 22 (1995), 694. doi: 10.1109/ICCV.1995.466871. Google Scholar [7] T. F. Chan, B. Y. Sandberg and L. A. Vese, Active contours without edges for vector-valued images,, Journal of Visual Communication and Image Representation, 11 (2000), 130. doi: 10.1006/jvci.1999.0442. Google Scholar [8] T. F. Chan and L. A. Vese, Active contours without edges,, IEEE Transactions on Image Processing, 10 (2001), 266. doi: 10.1109/83.902291. Google Scholar [9] G. Chung and L. A. Vese, Image segmentation using a multilayer level-set approach,, Computing and Visualization in Science, 12 (2009), 267. doi: 10.1007/s00791-008-0113-1. Google Scholar [10] L. D. Cohen and R. Kimmel, Global minimum for active contour models: A minimal path approach,, International Journal of Computer Vision, 24 (1997), 57. Google Scholar [11] M. G. Crandall, L. C. Evans and R. F. Gariepy, Optimal Lipschitz extensions and the infinity Laplacian,, Calculus of Variations and Partial Differential Equations, 13 (2001), 123. Google Scholar [12] G. Dal Maso, J. M. Morel and S. Solimini, A variational method in image segmentation: Existence and approximation results,, Acta Mathematica, 168 (1992), 89. doi: 10.1007/BF02392977. Google Scholar [13] L. C. Evans and R. F. Gariepy, Measure Theory and Fine Properties of Functions,, CRC Press, (1992). Google Scholar [14] L. C. Evans and Y. Yu, Various properties of solutions of the Infinity-Laplacian equation,, Communications in Partial Differential Equations, 30 (2005), 1401. doi: 10.1080/03605300500258956. Google Scholar [15] E. De Giorgi, M. Carriero and A. Leaci, Existence theorem for a minimum problem with free discontinuity set,, Archive for Rational Mechanics and Analysis, 108 (1989), 195. doi: 10.1007/BF01052971. Google Scholar [16] M. Jung, G. Chung, G. Sundaramoorthi, L. A. Vese and A. L. Yuille, Sobolev gradients and joint variational image segmentation, denoising, and deblurring,, IS&T/SPIE Electronic Imaging, 7246 (2009). doi: 10.1117/12.806067. Google Scholar [17] M. Kass, A. Witkin and D. Terzopoulos, Snakes: Active contour models,, International Journal of Computer Vision, 1 (1988), 321. doi: 10.1007/BF00133570. Google Scholar [18] M. S. Keegan, B. Sandberg and T. F. Chan, A multiphase logic framework for multichannel image segmentation,, Inverse Problems and Imaging, 6 (2012), 95. doi: 10.3934/ipi.2012.6.95. Google Scholar [19] S. Kichenassamy, A. Kumar, P. Olver, A. Tannenbaum and A. Yezzi, Gradient flows and geometric active contour models,, In Computer Vision, (1995), 810. doi: 10.1109/ICCV.1995.466855. Google Scholar [20] R. Kimmel and A. M. Bruckstein, Regularized Laplacian zero crossings as optimal edge integrators,, International Journal of Computer Vision, 53 (2001), 225. Google Scholar [21] C. Lacoste, X. Descombes and J. Zerubia, Unsupervised line network extraction in remote sensing using a polyline process,, Pattern Recognition, 43 (2010), 1631. doi: 10.1016/j.patcog.2009.11.003. Google Scholar [22] C. Larsen, C. Richardson and M. Sarkis, A Level Set Method for the Mumford -Shah Functional and Fracture,, Inst. Nacional de Matemática Pura e Aplicada, (2008). Google Scholar [23] S. Leung and H. Zhao, A grid based particle method for evolution of open curves and surfaces,, Journal of Computational Physics, 228 (2009), 7706. doi: 10.1016/j.jcp.2009.07.017. Google Scholar [24] W. H. Liao, L. Vese, S. C. Huang, M. Bergsneider and S. Osher, Computational anatomy and implicit object representation: A level set approach,, In Biomedical Image Registration, 2717 (2003), 40. doi: 10.1007/978-3-540-39701-4_5. Google Scholar [25] G. Lu and P. Wang, Inhomogeneous infinity Laplace equation,, Advances in Mathematics, 217 (2008), 1838. doi: 10.1016/j.aim.2007.11.020. Google Scholar [26] J. Melonakos, E. Pichon, S. Angenent and A. Tannenbaum, Finsler active contours,, Pattern Analysis and Machine Intelligence, 30 (2008), 412. doi: 10.1109/TPAMI.2007.70713. Google Scholar [27] J. M. Morel and S. Solimini, Segmentation of images by variational methods: A constructive approach,, Revista Matemática de la Universidad Complutense de Madrid, 1 (1988), 169. Google Scholar [28] J. M. Morel and S. Solimini, Segmentation d'images par méthode variationnelle: Une preuve constructive d'existence,, Comptes rendus de l'Académie des sciences. Série 1, 308 (1989), 465. Google Scholar [29] D. Mumford and J. Shah, Optimal approximations by piecewise smooth functions and associated variational problems,, Communications on Pure and Applied Mathematics, 42 (1989), 577. doi: 10.1002/cpa.3160420503. Google Scholar [30] J. W. Neuberger, Sobolev Gradients and Differential Equations,, Lecture Notes in Mathematics, (2010). doi: 10.1007/978-3-642-04041-2. Google Scholar [31] C. Niemann, A. S. Bondarenko, C. G. Constantin, E. T. Everson, K. A. Flippo, S. A. Gaillard, R. P. Johnson, S. A. Letzring, D. S. Montgomery, L. A. Morton, D. B. Schaeffer, T. Shimada and D. Winske, Collisionless shocks in a large magnetized laser-plasma plume,, Plasma Science, 39 (2011), 2406. doi: 10.1109/TPS.2011.2162007. Google Scholar [32] A. M. Oberman, A convergent difference scheme for the infinity laplacian: Construction of absolutely minimizing Lipschitz extensions,, Mathematics of Computation, 74 (2005), 1217. doi: 10.1090/S0025-5718-04-01688-6. Google Scholar [33] S. Osher and J. A. Sethian, Fronts propagating with curvature-dependent speed: Algorithms based on Hamilton-Jacobi formulations,, Journal of Computational Physics, 79 (1988), 12. doi: 10.1016/0021-9991(88)90002-2. Google Scholar [34] R. J. Renka, A simple explanation of the Sobolev gradient method,, Unpublished, (2006). Google Scholar [35] W. B. Richardson, Sobolev gradient preconditioning for image-processing PDEs,, Communications in Numerical Methods in Engineering, 24 (2008), 493. doi: 10.1002/cnm.951. Google Scholar [36] H. Schaeffer and L. Vese, Active contours with free endpoints,, Journal of Mathematical Imaging and Vision, 49 (2014), 20. doi: 10.1007/s10851-013-0437-4. Google Scholar [37] P. Smereka, Spiral crystal growth,, Physica D: Nonlinear Phenomena, 138 (2000), 282. doi: 10.1016/S0167-2789(99)00216-X. Google Scholar [38] G. Sundaramoorthi, A. Yezzi and A. C. Mennucci, Sobolev active contours,, Lecture Notes in Computer Science, 3752 (2005), 109. doi: 10.1007/11567646_10. Google Scholar [39] A. Tsai, A. Yezzi Jr and A. S. Willsky, Curve evolution implementation of the Mumford-Shah functional for image segmentation, denoising, interpolation, and magnification,, Image Processing, 10 (2001), 1169. doi: 10.1109/83.935033. Google Scholar [40] L. A. Vese and T. F. Chan, A multiphase level set framework for image segmentation using the Mumford and Shah model,, International Journal of Computer Vision, 50 (2002), 271. Google Scholar [41] C. Zach, L. Shan and M. Niethammer, Globally optimal Finsler active contours,, In Pattern Recognition, 5748 (2009), 552. doi: 10.1007/978-3-642-03798-6_56. Google Scholar
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