Algorithms

The CREASEG software allows to evaluate the performance of six level-set based segmentation algorithms in the context of image processing. These methods have been chosen in order to work with a wide range of level-sets.

Note that if you are publishing any work, where this program has been used, or which used one of the given level-set algorithms, please remember that you must reference the papers cited above and the name of the CREASEG software must be mentioned in the publication.

CREASEG sofware

"T. Dietenbeck, M. Alessandrini, D. Friboulet, O. Bernard. CREASEG: a free software for the evaluation of image segmentation algorithms based on level-set. In IEEE International Conference On Image Processing. Hong Kong, China, 2010."

Bernard method

"O. Bernard, D. Friboulet, P. Thevenaz, M. Unser. Variational B-Spline Level-Set: A Linear Filtering Approach for Fast Deformable Model Evolution. In IEEE Transactions on Image Processing. volume 18, no. 06, pp. 1179-1191, 2009."

Caselles method

"V. Caselles, R. Kimmel, and G. Sapiro. Geodesic active contours. International Journal of Computer Vision, volume 22, pp. 61-79, 1997."

Chan & Vese method

"T. Chan and L. Vese. Active contours without edges. IEEE Transactions on Image Processing. volume10, pp. 266-277, February 2001."

Lankton method

"S. Lankton, A. Tannenbaum. Localizing Region-Based Active Contours. In IEEE Transactions on Image Processing. volume 17, no. 11, pp. 2029-2039, 2008."

Li method

"C. Li, C.Y. Kao, J.C. Gore, Z. Ding. Minimization of Region-Scalable Fitting Energy for Image Segmentation. In IEEE Transactions on Image Processing. volume 17, no. 10, pp. 1940-1949, 2008."

Shi method

"Yonggang Shi, William Clem Karl. A Real-Time Algorithm for the Approximation of Level-Set-Based Curve Evolution. In IEEE Transactions on Image Processing. volume 17, no. 05, pp. 645-656, 2008."