ChanVeseBinarize

ChanVeseBinarize[image]
finds a two-level segmentation of image by computing optimal contours around regions of consistent intensity in image.

ChanVeseBinarize[image,marker]
uses marker to create an initial contour.

ChanVeseBinarize[image,marker,{μ,ν,λ1,λ2}]
specify the Chan-Vese weights μ, ν, , and .

Details and OptionsDetails and Options

  • ChanVeseBinarize implements an iterative active contour method to achieve a two-level segmentation of image.
  • ChanVeseBinarize works with arbitrary 2D as well as 3D images.
  • The target region marker can be any of the following:
  • markerimagea marker image
    {pos1,pos2,}a list of positions
    fgcolorforeground color
    {{fgcolor,bgcolor}}foreground and background colors
  • Positions are assumed to be in the standard image coordinate system.
  • ChanVeseBinarize uses the Euclidean distance between channel vectors to determine the similarity between pixels inside and outside of the contour.
  • The ChanVese segmentation of an image domain into the two segments and with contour minimizes the following functional of image :
  • F(c_1,c_2,Gamma)=mu Length[Gamma]+nu Area(D)+lambda_1int_DTemplateBox[{{f, -, {c, _, 1}}}, Abs]^2dxdy+lambda_2int_(Omega\D)TemplateBox[{{f, -, {c, _, 2}}}, Abs]^2dxdy
  • The functional is parametrized by the length penalty , the area penalty , and level penalties and .
  • The ChanVese algorithm partitions image such that the first segment will differ as little as possible from constant and the second segment will deviate as little as possible from constant . If constants and are not specified, one assumes c1=Mean[f] in , and c2=Mean[f] in .
  • The contour between the two resulting segments and will exhibit a short length for , and for the area of will tend to be small or for tend to be large.
  • ChanVeseBinarize iteratively minimizes a functional that is a weighted sum of the contour length, the enclosed area, and the deviation between the image and the two-level segmentation.
  • The maximum number of iteration steps is given by the MaxIterations option with default setting 100.
Introduced in 2010
(8.0)
| Updated in 2014
(10.0)