可以直接运行的matlab程序，很好用，开源代码，直接运行效果很好，也可以根据自己的需要进行改进。很棒的！ 可以直接运行的matlab程序，很好用，开源代码，直接运行效果很好，也可以根据自己的需要进行改进。很棒的！

自己编的，基于椭圆形状约束的主动轮廓分割模型进行眼底图像视盘分割，matlab code

Snake模型与先检测边缘点再将它们连接成边缘的方法不同，轮廓的连通性及角点均影响能量泛函。Snake的轮廓线模型继承了上层知识，而轮廓线与目标轮廓的匹配又结合了底层特征。Snake模型可以通过优化能量泛函得到一个局部最优的轮廓曲线。

1、代码别人写的，自己备份 2、手动标记初始化边缘。 3、按"S",停止标记点，开始搜索 4、最终显示搜索结果

自己写的利用贪婪算法获取收敛轮廓的主动轮廓算法matlab程序，可以实现自动初始化轮廓，并且初始轮廓不需要全部包含目标。 压缩包中包括：matlab程序，运行说明及参考文献 希望对学习active contour 的您有用~~

可以直接运行的matlab程序，很好用，开源代码，直接运行效果很好，也可以根据自己的需要进行改进。很棒的！

The *Morphological Snakes* are a family of related methods for image-guided evolution of curves and surfaces represented as a level-set of an embedding function. They have application in several computer vision areas, such as tracking and image segmentation.

使用GVF域和VFC域进行图片分割 % Vector field convolution (VFC) external force field example. % % See also AMT, EXAMPLE_PIG, AM_VFC, AM_VFK, AC_DISPLAY. % % Reference % [1] Bing Li and Scott T. Acton, "Active contour external force using % vector field convolution for image segmentation," Image Processing, % IEEE Trans. on, vol. 16, pp. 2096-2106, 2007. % [2] Bing Li and Scott T. Acton, "Automatic Active Model % Initialization via Poisson Inverse Gradient," Image Processing, % IEEE Trans. on, vol. 17, pp. 1406-1420, 2008. % % (c) Copyright Bing Li 2005 - 2009. clear all disp('======================================') disp('Vector field convolution (VFC) example') %% parameter settings disp('Initializing parameters ...') SAVE_AVI = 0; % set it to 1 if you want to save the process as .avi movie DISPLAY_STREAMLINE = 0; % set it to 1 if you want to plot streamlines, note that it takes a while mu = .2; GVF_ITER = 100; normalize = 1; alpha = .5; beta = 0; tau = .5; SNAKE_ITER = 5; SNAKE_ITER1 = 60; RES = .5; clr = {'b' 'b' 'r'}; %% Read images disp('Reading images ...') U = imread('im_U.bmp'); noisyU=imread('im_Unoisy.bmp'); figure(1) %% compare 3 different cases for cs = 1:3, %% compute external force fields switch cs, case 1, % traditional GVF with Gaussian filter disp('--------------------------------------------------') disp('Case 1: GVF snake with initial circle close to FOI') disp('Computing the external force field ...') h = fspecial('gaussian',[5 5],5); f = imfilter(double(noisyU),h); titl = 'GVF'; Fext = AM_GVF(f, mu, GVF_ITER, normalize); R = 20; case 2, % traditional GVF with Gaussian filter disp('--------------------------------------------------') disp('Case 2: GVF snake with initial circle far away from FOI') disp('Computing the external force field ...

简单，明确，适合初学者，代码可以直接运行，自带图片

贪心算法，opencv，主动轮廓模型