Finsler active contours
Finsler active contours
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DOI：
10.1109/tpami.2007.70713
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发表时间：
2008-03-01
影响因子：
23.6
通讯作者：
Tannenbaum, Allen
中科院分区：
文献类型：
--
作者：
Melonakos, John;Pichon, Eric;Tannenbaum, Allen
在本文中，我们提出了一种图像分割技术的基础上增加的共形（或测地线）活动轮廓框架与方向信息。在各向同性的情况下，欧几里德度量局部地乘以基于图像信息的标量保形因子，使得位于感兴趣的点（通常是边缘）上的曲线的加权长度很小。所选择的共形因子仅取决于位置，并且在这个意义上是各向同性的。虽然方向信息已经研究了以前的其他分割框架，在这里，我们表明，如果一个人希望添加方向性的共形活动轮廓框架，然后得到一个定义良好的最小化问题的情况下，该因素定义了芬斯勒度量。最佳曲线可以使用变分法或基于动态规划的方案来获得。最后，我们通过从航空图像中提取道路，从医学血管造影照片中提取血管，从扩散加权磁共振图像中提取神经束来演示该技术。
In this paper, we propose an image segmentation technique based on augmenting the conformal (or geodesic) active contour framework with directional information. In the isotropic case, the euclidean metric is locally multiplied by a scalar conformal factor based on image information such that the weighted length of curves lying on points of interest (typically edges) is small. The conformal factor that is chosen depends only upon position and is in this sense isotropic. Although directional information has been studied previously for other segmentation frameworks, here, we show that if one desires to add directionality in the conformal active contour framework, then one gets a well-defined minimization problem in the case that the factor defines a Finsler metric. Optimal curves may be obtained using the calculus of variations or dynamic programming-based schemes. Finally, we demonstrate the technique by extracting roads from aerial imagery, blood vessels from medical angiograms, and neural tracts from diffusion-weighted magnetic resonance imagery.