DocumentCode
866237
Title
Multigrid Geometric Active Contour Models
Author
Papandreou, George ; Maragos, Petros
Author_Institution
Sch. of Electr. & Comput. Eng., Nat. Tech. Univ. of Athens
Volume
16
Issue
1
fYear
2007
Firstpage
229
Lastpage
240
Abstract
Geometric active contour models are very popular partial differential equation-based tools in image analysis and computer vision. We present a new multigrid algorithm for the fast evolution of level-set-based geometric active contours and compare it with other established numerical schemes. We overcome the main bottleneck associated with most numerical implementations of geometric active contours, namely the need for very small time steps to avoid instability, by employing a very stable fully 2-D implicit-explicit time integration numerical scheme. The proposed scheme is more accurate and has improved rotational invariance properties compared with alternative split schemes, particularly when big time steps are utilized. We then apply properly designed multigrid methods to efficiently solve the occurring sparse linear system. The combined algorithm allows for the rapid evolution of the contour and convergence to its final configuration after very few iterations. Image segmentation experiments demonstrate the efficiency and accuracy of the method
Keywords
computer vision; geometry; image segmentation; integration; partial differential equations; 2D implicit-explicit time integration; computer vision; image analysis; image segmentation; level-set-based geometric active contours; multigrid geometric active contour models; partial differential equation; sparse linear system; Active contours; Computer vision; Convergence; Design methodology; Differential equations; Image analysis; Linear systems; Multigrid methods; Partial differential equations; Solid modeling; Geometric active contours; image segmentation; implicit-explicit schemes; level sets; multigrid; partial differential equations; Algorithms; Computer Simulation; Image Enhancement; Image Interpretation, Computer-Assisted; Information Storage and Retrieval; Models, Statistical;
fLanguage
English
Journal_Title
Image Processing, IEEE Transactions on
Publisher
ieee
ISSN
1057-7149
Type
jour
DOI
10.1109/TIP.2006.884952
Filename
4032824
Link To Document