Title :
Level Set Constrained Segmentation Using Local Curvature
Author :
Djabelkhir, Fahima ; Khamadja, Mohammed ; Odet, Christophe
Author_Institution :
Univ. of Jijel, Jijel
Abstract :
A novel method for level set based segmentation of images using constrains depending on image characteristics is presented. Our method is motivated by the fact that due to the un homogeneity of image regions, segmentation algorithms often fail because the final contour should depend in those regions. We propose to add constrains, to level set equation, depending in image characteristics. We apply a local coefficient depending on curvature in a local neighbourhood at each point. So the final contour is more homogenous with smoothed regions and more curved regions. In addition, as the stop forces in basic level set equation are not enough to stop propagation in weak edges, we propose to begin by adding surface minimization and region intensity constrains to improve the propagation of the final contour. The surface minimization term proves stabilization efficiency even in presence of nosy and weak boundary. Results illustrated with a medical image demonstrate the efficiency of the method.
Keywords :
edge detection; image segmentation; medical image processing; contour evolution; edge detection; level set constrained segmentation; level set equation; local curvature; medical image; stabilization efficiency; surface minimization; Active contours; Biomedical imaging; Deformable models; Equations; Geophysics computing; Image edge detection; Image segmentation; Level set; Statistics; Topology;
Conference_Titel :
Image and Signal Processing and Analysis, 2007. ISPA 2007. 5th International Symposium on
Conference_Location :
Istanbul
Print_ISBN :
978-953-184-116-0
DOI :
10.1109/ISPA.2007.4383681