preprintNov 19, 2002Closed access
Gradient flows and geometric active contour models
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Abstract
In this paper, we analyze the geometric active contour models discussed previously from a curve evolution point of view and propose some modifications based on gradient flows relative to certain new feature-based Riemannian metrics. This leads to a novel snake paradigm in which the feature of interest may be considered to lie at the bottom of a potential well. Thus the snake is attracted very naturally and efficiently to the desired feature. Moreover, we consider some 3-D active surface models based on these ideas.>
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660
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- FWCI
- 71.08
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- 100%
- References
- 28
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5Topics & keywords
Topics
Keywords
- Feature (linguistics)
- Active contour model
- Point (geometry)
- Artificial intelligence
- Computer science
- Computer vision
- Image (mathematics)
- Pattern recognition (psychology)
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