3rd International Conference on Control, Engineering & Information Technology CEIT’2015 Tlemcen, Algeria, 25-27 May, 2015.
Fast Algorithm to Minimize model Combining Dynamically Local and Global Fitting Energy
for Image Segmentation
Yamina Boutiche
Welding and NDT Research Centre (C.S.C.) Image and Signal Processing Laboratory,
Route de Dely-Ibrahim BP 64 Ch´eraga, 16300 Algiers, Algeria.
Email: [email protected]
Abstract—Segmentation by using region-based deformable models has known a great success and large domain of applications. In this paper, we propose a fast algorithm to minimise model which combines local fitting energy and global fitting energy. The minimisation via the proposed algorithm avoids solving any Partial Differential Equation PDE. Consequently, there is no need to any stability conditions. Furthermore, owing to the fast convergence we don’t need to the re-initialisation step and the term that keeps Level Set LS as Signed Distance Function SDF. In addition, we have used a dynamic function to adjust between the local and global energies. Successful segmentation results are obtained on synthetic and real images with a great saving of CPU time compared to the minimisation via gradient descent method.
Index Terms—Image segmentation; region-based model; level set; hybrid models; sweeping;
fast convergence.
