Speed Improvement of B-Snake Algorithm Using Dynamic Programming Optimization

This paper presents a novel approach to contour approximation carried out by means of the B-snake algorithm and the dynamic programming (DP) optimization technique. Using the proposed strategy for contour point search procedure, computing complexity is reduced to O(N × M2), whereas the standard DP method has an O(N × M4) complexity, with N being the number of contour sample points and M being the number of candidates in the search space. The storage requirement was also decreased from N × M3 to N × M memory elements. Some experiments on noise corrupted synthetic image, magnetic resonance, and computer tomography medical images have shown that the proposed approach results are equivalent to those obtained by the standard DP algorithm.

[1]  Michael Unser,et al.  B-spline snakes: a flexible tool for parametric contour detection , 2000, IEEE Trans. Image Process..

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

[3]  K. Lam,et al.  Fast greedy algorithm for active contours , 1994 .

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

[5]  Eam Khwang Teoh,et al.  Dynamic B-snake model for complex objects segmentation , 2005, Image Vis. Comput..

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

[7]  Ravinda G. N. Meegama,et al.  NURBS snakes , 2003, Image Vis. Comput..

[8]  Demetri Terzopoulos,et al.  United Snakes , 1999, Medical Image Anal..

[9]  A Aldroubi,et al.  Multi-scale B-spline Snakes for General Contour Detection , 2001 .

[10]  Thierry Blu,et al.  Efficient energies and algorithms for parametric snakes , 2004, IEEE Transactions on Image Processing.

[11]  P. B. Coaker,et al.  Applied Dynamic Programming , 1964 .

[12]  Jerry L. Prince,et al.  Gradient vector flow: a new external force for snakes , 1997, Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

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

[14]  P. Jaccard.  THE DISTRIBUTION OF THE FLORA IN THE ALPINE ZONE.1 , 1912 .

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

[16]  Amir A. Amini,et al.  Quantitative coronary angiography with deformable spline models , 1997, IEEE Transactions on Medical Imaging.

[17]  Amir A. Amini,et al.  Snakes and Splines for Tracking Non-Rigid Heart Motion , 1996, ECCV.

[18]  Michael Unser,et al.  Splines: a perfect fit for signal and image processing , 1999, IEEE Signal Process. Mag..

[19]  Dong Joong Kang,et al.  A fast and stable snake algorithm for medical images , 1999, Pattern Recognition Letters.

[20]  Tomas Gustavsson,et al.  A multiscale dynamic programming procedure for boundary detection in ultrasonic artery images , 2000, IEEE Transactions on Medical Imaging.