Image segmentation using active contours: Calculus of variations or shape gradients?

被引:137
作者
Aubert, G
Barlaud, M
Faugeras, O
Jehan-Besson, S
机构
[1] UNSA, CNRS, Lab Dieudonne, F-06108 Nice 2, France
[2] UNSA, CNRS, Lab I3S, F-06903 Sophia Antipolis, France
[3] INRIA Sophia Antipolis, F-06902 Sophia Antipolis, France
关键词
image segmentation; region segmentation; active contours; active regions; image statistics; region functionals; boundary functionals; calculus of variations; shape optimization; shape gradient; Euler-Lagrange equations; Gateaux derivative; Parzen window estimation; level set methods;
D O I
10.1137/S0036139902408928
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
We consider the problem of segmenting an image through the minimization of an energy criterion involving region and boundary functionals. We show that one can go from one class to the other by solving Poisson's or Helmholtz's equation with well-chosen boundary conditions. Using this equivalence, we study the case of a large class of region functionals by standard methods of the calculus of variations and derive the corresponding Euler - Lagrange equations. We revisit this problem using the notion of a shape derivative and show that the same equations can be elegantly derived without going through the unnatural step of converting the region integrals into boundary integrals. We also de. ne a larger class of region functionals based on the estimation and comparison to a prototype of the probability density distribution of image features and show how the shape derivative tool allows us to easily compute the corresponding Gateaux derivatives and Euler - Lagrange equations. Finally we apply this new functional to the problem of regions segmentation in sequences of color images. We briefly describe our numerical scheme and show some experimental results.
引用
收藏
页码:2128 / 2154
页数:27
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