DocumentCode
984796
Title
Constraining active contour evolution via Lie Groups of transformation
Author
Mansouri, Abdol-Reza ; Mukherjee, Dipti Prasad ; Acton, Scott T.
Author_Institution
Div. of Eng. & Appl. Sci., Harvard Univ., Cambridge, MA, USA
Volume
13
Issue
6
fYear
2004
fDate
6/1/2004 12:00:00 AM
Firstpage
853
Lastpage
863
Abstract
We present a novel approach to constraining the evolution of active contours used in image analysis. The proposed approach constrains the final curve obtained at convergence of curve evolution to be related to the initial curve from which evolution begins through an element of a desired Lie group of plane transformations. Constraining curve evolution in such a way is important in numerous tracking applications where the contour being tracked in a certain frame is known to be related to the contour in the previous frame through a geometric transformation such as translation, rotation, or affine transformation, for example. It is also of importance in segmentation applications where the region to be segmented is known up to a geometric transformation. Our approach is based on suitably modifying the Euler-Lagrange descent equations by using the correspondence between Lie groups of plane actions and their Lie algebras of infinitesimal generators, and thereby ensures that curve evolution takes place on an orbit of the chosen transformation group while remaining a descent equation of the original functional. The main advantage of our approach is that it does not necessitate any knowledge of nor any modification to the original curve functional and is extremely straightforward to implement. Our approach therefore stands in sharp contrast to other approaches where the curve functional is modified by the addition of geometric penalty terms. We illustrate our algorithm on numerous real and synthetic examples.
Keywords
Lie algebras; Lie groups; image segmentation; image sequences; transforms; Euler-Lagrange equation; Lie algebra; Lie group; curve evolution equation; geometric transformation; image analysis; plane transformations; Active contours; Active shape model; Algebra; Convergence; Councils; Deformable models; Image segmentation; Image sequence analysis; Image sequences; Nonlinear equations; Algorithms; Artificial Intelligence; Computer Simulation; Image Enhancement; Image Interpretation, Computer-Assisted; Numerical Analysis, Computer-Assisted; Pattern Recognition, Automated; Reproducibility of Results; Sensitivity and Specificity; Signal Processing, Computer-Assisted; Subtraction Technique;
fLanguage
English
Journal_Title
Image Processing, IEEE Transactions on
Publisher
ieee
ISSN
1057-7149
Type
jour
DOI
10.1109/TIP.2004.826128
Filename
1298841
Link To Document