The geodesic distance-based dual-front curve evolution model is a powerful and efficient solution to the active contours and image segmentation issues. In its basic formulation , the dual-front model regards the meeting interfaces of two adjacent Voronoi regions as the evolving curves in the course of curve evolution. One of the most crucial ingredients for the construction of Voronoi regions or Voronoi diagram is the geodesic metrics  and the corresponding geodesic distance . In this paper, we introduce a new type of geodesic metrics that encodes the edge-based anisotropy features, the region-based homogeneity penalization and asymmetric enhancement. In contrast to the original isotropic dual-front model, the use of the asymmetric enhancement can reduce the risk of shortcuts or leakage problems especially when the initial curves are far away from the target boundaries  . Moreover, the proposed dual-front model can be applied for image segmentation in conjunction with various region-based homogeneity terms , whereas the original model only makes use of the piecewise constant case . The numerical experiments on both synthetic and real images show that the proposed  model indeed achieves encouraging results.
The Voronoi diagram-based dual-front active contour models are known as a powerful and efficient way for addressing the image segmentation and domain partitioning problems. In the basic formulation of the dual-front models, the evolving contours can be considered as the interfaces of adjacent Voronoi regions . Among these dual-front models, a crucial ingredient is regarded as the geodesic metrics by which the geodesic distances and the corresponding Voronoi diagram can be estimated . In this paper, we introduce a type of asymmetric quadratic metrics dual-front model. The metrics considered are built by the integration of the image features and a vector field derived from the evolving contours. The use of the asymmetry enhancement can reduce the risk of contour shortcut or leakage problems especially when the initial contours are far away from the target boundaries or the images have complicated intensity distributions . Moreover, the proposed dual-front model can be applied for image segmentation in conjunction with various region-based homogeneity terms . The numerical experiments on both synthetic and real images show that the proposed dual-front model indeed achieves encouraging results.
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geodesic distance-based
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curve evolution model is
active contour models are known as
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solution to the active contours and image segmentation issues. In its basic formulation ,
way for addressing the image segmentation and domain partitioning problems. In the basic formulation of
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model regards the meeting interfaces of two
models, the evolving contours can be considered as the interfaces of
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as the evolving curves in the course of curve evolution. One of the most crucial ingredients for the construction of Voronoi regions or Voronoi diagram is
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by which the geodesic distances
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geodesic distance
Voronoi diagram can be estimated
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new type of geodesic metrics that encodes the edge-based anisotropy features, the region-based homogeneity penalization and asymmetric enhancement. In contrast to the original isotropic
type of asymmetric quadratic metrics
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model, the
model. The metrics considered are built by the integration of the image features and a vector field derived from the evolving contours. The
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asymmetric
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or the images have complicated intensity distributions
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, whereas the original model only makes use of the piecewise constant case
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dual-front