DocumentCode
2116710
Title
Level Set Constrained Segmentation Using Local Curvature
Author
Djabelkhir, Fahima ; Khamadja, Mohammed ; Odet, Christophe
Author_Institution
Univ. of Jijel, Jijel
fYear
2007
fDate
27-29 Sept. 2007
Firstpage
152
Lastpage
155
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;
fLanguage
English
Publisher
ieee
Conference_Titel
Image and Signal Processing and Analysis, 2007. ISPA 2007. 5th International Symposium on
Conference_Location
Istanbul
ISSN
1845-5921
Print_ISBN
978-953-184-116-0
Type
conf
DOI
10.1109/ISPA.2007.4383681
Filename
4383681
Link To Document