Fast marching the global minimum of active contours

A new approach of edge integration for shape modeling is presented. It is used to find the global minimum of an active contour model's energy between two points. Initialization is made easier and the curve is not trapped at a local minimum by spurious edges. We modify the "snake" energy by including the internal regularization term in the external potential term. Our method is based on the interpretation of the snake as a path of minimal length in a Riemannian metric, or as a path of minimal weighted distance. We then make use of a new numerical method to find the shortest path which is the global minimum of the energy among all paths joining the two endpoints. We show examples of our method applied to real aerial and medical images.

[1]  J. Meigs,et al.  WHO Technical Report , 1954, The Yale Journal of Biology and Medicine.

[2]  Ugo Montanari,et al.  On the optimal detection of curves in noisy pictures , 1971, CACM.

[3]  Martin A. Fischler,et al.  Detection of roads and linear structures in low-resolution aerial imagery using a multisource knowledge integration technique☆ , 1981 .

[4]  M. A. Jaswon.  A Review of the Theory , 1984 .

[5]  G. Borgefors.  Distance transformations in arbitrary dimensions , 1984 .

[6]  J. Sethian,et al.  Fronts propagating with curvature-dependent speed: algorithms based on Hamilton-Jacobi formulations , 1988 .

[7]  S. Osher,et al.  Algorithms Based on Hamilton-Jacobi Formulations , 1988 .

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

[9]  Sharat Chandran,et al.  Global minima via dynamic programming: energy minimizing active contours , 1991, Optics & Photonics.

[10]  E. Rouy,et al.  A viscosity solutions approach to shape-from-shading , 1992 .

[11]  Gábor Székely,et al.  Estimating shortest paths and minimal distances on digitized three-dimensional surfaces , 1993, Pattern Recognit..

[12]  Josiane Zerubia,et al.  New prospects in line detection for remote sensing images , 1994, Proceedings of ICASSP '94. IEEE International Conference on Acoustics, Speech and Signal Processing.

[13]  Alfred M. Bruckstein,et al.  Finding Shortest Paths on Surfaces Using Level Sets Propagation , 1995, IEEE Trans. Pattern Anal. Mach. Intell..

[14]  Ron Kimmel,et al.  Finding shortest paths on surfaces by fast global approximation and precise local refinement , 1995, Other Conferences.

[15]  Ron Kimmel,et al.  Fast Marching Methods for Computing Distance Maps and Shortest Paths , 1996 .

[16]  Laurent D. Cohen,et al.  Global Minimum for Active Contour Models: A Minimal Path Approach , 1996, Proceedings CVPR IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[17]  Ron Kimmel,et al.  Finding The Shortest Paths on Surfaces by Fast Global Approximation and Precise Local Refinement , 1996, Int. J. Pattern Recognit. Artif. Intell..

[18]  James A. Sethian,et al.  Theory, algorithms, and applications of level set methods for propagating interfaces , 1996, Acta Numerica.

[19]  J A Sethian,et al.  A fast marching level set method for monotonically advancing fronts. , 1996, Proceedings of the National Academy of Sciences of the United States of America.