Abstract
Polar active contours have proven to be a powerful segmentation method for many medical as well as other computer vision applications, such as interactive image segmentation or tracking. Inspired by recent work on Sobolev active contours we derive a Sobolev-type function space for polar curves, which is endowed with a metric that allows us to favor origin translations and scale changes over smooth deformations of the curve. The resulting translation, scale, and deformation weighted polar active contours inherit the coarse-to-fine behavior of Sobolev active contours as well as their robustness to local minima and are thus very useful for many medical applications, such as cross-sectional vessel segmentation, aneurysm analysis, or cell tracking.
Original language | English |
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Pages (from-to) | 354-365 |
Number of pages | 12 |
Journal | Journal of Mathematical Imaging and Vision |
Volume | 44 |
Issue number | 3 |
DOIs | |
Publication status | Published - Nov 2012 |
Externally published | Yes |
Keywords
- Active contours
- Curve evolution
- Image segmentation
- Sobolev spaces