FACE: fast active-contour curvature-based evolution

This paper presents an active contour model for fast object segmentation called FACE. A novel energy term that takes into account the computational complexity of the active contour is introduced together with related constraints and minimization procedure. The described process is based on the regularization and optimization of the active contour control points position. The trade-off between computational complexity and final contour accuracy is based on curvature estimation. The result is a fast active contour convergence towards desired object boundaries. This method can be combined with most of the other active contour approaches presented in literature, thanks to the independence between the computational minimization process and the classical active contour minimization process. The object segmentation procedure can be automatic or semiautomatic depending on the original image complexity. Several tests and experiments have been realized. Results show improvements in terms of computational time reduction when compared with other similar active contour models.

[1]  Roman Goldenberg,et al.  Fast Geodesic Active Contours , 1999, Scale-Space.

[2]  C VemuriBaba,et al.  Shape Modeling with Front Propagation , 1995 .

[3]  Natan Peterfreund The Velocity Snake: Deformable Contour for Tracking in Spatio-Velocity Space , 1999, Comput. Vis. Image Underst..

[4]  Farzin Mokhtarian,et al.  Improved curvature estimation for accurate localisation of active contours , 2001, Proceedings 2001 International Conference on Image Processing (Cat. No.01CH37205).

[5]  Demetri Terzopoulos,et al.  Deformable models in medical image analysis: a survey , 1996, Medical Image Anal..

[6]  Demetri Terzopoulos,et al.  Snakes: Active contour models , 2004, International Journal of Computer Vision.

[7]  Marie-Odile Berger Snake growing , 1990, ECCV.

[8]  D. Chopp Computing Minimal Surfaces via Level Set Curvature Flow , 1993 .

[9]  V. Caselles,et al.  A geometric model for active contours in image processing , 1993 .

[10]  Alok Gupta,et al.  Dynamic Programming for Detecting, Tracking, and Matching Deformable Contours , 1995, IEEE Trans. Pattern Anal. Mach. Intell..

[11]  Michel Barlaud,et al.  A 3-Step Algorithm Using Region-Based Active Contours for Video Objects Detection , 2002, EURASIP J. Adv. Signal Process..

[12]  Jayant Shah,et al.  A common framework for curve evolution, segmentation and anisotropic diffusion , 1996, Proceedings CVPR IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[13]  Alan L. Yuille,et al.  Region Competition: Unifying Snakes, Region Growing, and Bayes/MDL for Multiband Image Segmentation , 1996, IEEE Trans. Pattern Anal. Mach. Intell..

[14]  Nahum Shimkin,et al.  Velocity-Guided Tracking of Deformable Contours in Three Dimensional Space , 2000, ECCV.

[15]  Michael Isard,et al.  Active Contours , 2000, Springer London.

[16]  Jerry L. Prince,et al.  Snakes, shapes, and gradient vector flow , 1998, IEEE Trans. Image Process..

[17]  G. Sapiro,et al.  Geometric partial differential equations and image analysis [Book Reviews] , 2001, IEEE Transactions on Medical Imaging.

[18]  Wolfgang Effelsberg,et al.  Fast Implicit Active Contour Models , 2002, DAGM-Symposium.

[19]  J. Sethian,et al.  FRONTS PROPAGATING WITH CURVATURE DEPENDENT SPEED: ALGORITHMS BASED ON HAMILTON-JACOB1 FORMULATIONS , 2003 .

[20]  Douglas P. Perrin,et al.  Rethinking classical internal forces for active contour models , 2001, Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001.

[21]  Guillermo Sapiro,et al.  Morphing Active Contours , 2000, IEEE Trans. Pattern Anal. Mach. Intell..

[22]  Anil K. Jain,et al.  Object Tracking Using Deformable Templates , 1998, ICCV.

[23]  Scott T. Acton,et al.  Merging parametric active contours within homogeneous image regions for MRI-based lung segmentation , 2003, IEEE Transactions on Medical Imaging.

[24]  Steve R. Gunn,et al.  A Robust Snake Implementation; A Dual Active Contour , 1997, IEEE Trans. Pattern Anal. Mach. Intell..

[25]  Demetri Terzopoulos,et al.  On Matching Deformable Models to Images , 1987, Topical Meeting on Machine Vision.

[26]  Baba C. Vemuri,et al.  Shape Modeling with Front Propagation: A Level Set Approach , 1995, IEEE Trans. Pattern Anal. Mach. Intell..

[27]  Anthony J. Yezzi,et al.  Gradient flows and geometric active contour models , 1995, Proceedings of IEEE International Conference on Computer Vision.

[28]  S.T. Acton,et al.  Image segmentation by curve evolution with clustering , 2000, Conference Record of the Thirty-Fourth Asilomar Conference on Signals, Systems and Computers (Cat. No.00CH37154).

[29]  Akshay K. Singh,et al.  Deformable models in medical image analysis , 1996, Proceedings of the Workshop on Mathematical Methods in Biomedical Image Analysis.

[30]  Rachid Deriche,et al.  Geodesic Active Contours and Level Sets for the Detection and Tracking of Moving Objects , 2000, IEEE Trans. Pattern Anal. Mach. Intell..

[31]  Ramesh C. Jain,et al.  Using Dynamic Programming for Solving Variational Problems in Vision , 1990, IEEE Trans. Pattern Anal. Mach. Intell..

[32]  J. Sethian,et al.  A Fast Level Set Method for Propagating Interfaces , 1995 .

[33]  Demetri Terzopoulos,et al.  Deformable models , 2000, The Visual Computer.

[34]  Demetri Terzopoulos,et al.  T-snakes: Topology adaptive snakes , 2000, Medical Image Anal..

[35]  Janusz Konrad,et al.  Motion segmentation with level sets , 1999, Proceedings 1999 International Conference on Image Processing (Cat. 99CH36348).

[36]  Zeyun Yu,et al.  Image segmentation using gradient vector diffusion and region merging , 2002, Object recognition supported by user interaction for service robots.

[37]  Mubarak Shah,et al.  A Fast algorithm for active contours and curvature estimation , 1992, CVGIP Image Underst..

[38]  Roman Goldenberg,et al.  Cortex segmentation: a fast variational geometric approach , 2002, IEEE Transactions on Medical Imaging.

[39]  Daniele D. Giusto,et al.  ACTIVE CONTOUR FOR AUTOMATIC SEGMENTATION OF VIDEO SEQUENCES , 2003 .

[40]  Rémi Ronfard,et al.  Region-based strategies for active contour models , 1994, International Journal of Computer Vision.

[41]  Tony F. Chan,et al.  Active contours without edges , 2001, IEEE Trans. Image Process..

[42]  Laurent D. Cohen,et al.  Finite-Element Methods for Active Contour Models and Balloons for 2-D and 3-D Images , 1993, IEEE Trans. Pattern Anal. Mach. Intell..

[43]  Laurent D. Cohen,et al.  On active contour models and balloons , 1991, CVGIP Image Underst..

[44]  Guillermo Sapiro,et al.  Geodesic Active Contours , 1995, International Journal of Computer Vision.

[45]  Marcel Worring,et al.  Watersnakes: Energy-Driven Watershed Segmentation , 2003, IEEE Trans. Pattern Anal. Mach. Intell..

[46]  James A. Sethian,et al.  Level Set Methods and Fast Marching Methods , 1999 .

[47]  Daniele D. Giusto,et al.  A fast algorithm for video segmentation and object tracking , 2002, 2002 14th International Conference on Digital Signal Processing Proceedings. DSP 2002 (Cat. No.02TH8628).