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前沿：最近由于大论文实验的原因，需要整理几种Snake方法，以比较道路提取效果。所以今天晚上就将电脑中的一些LBF Snake代码作一下分类定义。并给出效果。以便比较。
原始的LBF算法实现如下；
实验的代码下载地址，Download Link。然后在网盘中找到这个目录
，然后找到下图所示的文件。
但是，初步测试是不能用，原因是LSE程序的源文件无法编译，找不到源文件。这个代码中提到的参考文献是[1]. 如果需要更加详细的学习，请直接百度学术中下载。
一下是原作者在代码中的一些说明：
% This Matlab code demomstrates an improved algorithm based on the local binary fitting (LBF) model % in Chunming Li et al‘s paper: % "Implicit Active Contours Driven By Local Binary Fitting Energy" in Proceedings of CVPR‘07 % % Author: Chunming Li, all rights reserved % E-mail: li_chunming@hotmail.com % URL: http://vuiis.vanderbilt.edu/~licm/ % http://www.engr.uconn.edu/~cmli/ % % Notes: % 1. Some parameters are set to default values for the demos in this package. They may need to be % modified for different types of images. % 2. The current version does not work for images with multiple junctions, due to its two-phase % formulation (i.e. using only one level set function). For example, an image has 3 objects/regions, % and each object/region is directly contiguous to all the other two objects/regions. This code will be % extended to multiphase in the future version, which will be available at the author‘s webpage. % 3. The image intensities may need to be rescaled to the range of [0, 255], if the intensities are much lower % or much higher than 255. Alternatively, you can change the parameters lambda1 and lambda2, and nu (the % coefficient of lenght term) accordingly.
2008年的文章的算法效果
原始图像
测试的实验结果图(文献[2])
实验的代码下载地址，Download Link。然后在网盘中找到这个目录
用原作者自己的一些话说明，则如下
% This Matlab file demomstrates a level set method in Chunming Li et al‘s paper % "Minimization of Region-Scalable Fitting Energy for Image Segmentation", % IEEE Trans. Image Processing, vol. 17 (10), pp.1940-1949, 2008. % Author: Chunming Li, all rights reserved % E-mail: li_chunming@hotmail.com % URL: http://www.engr.uconn.edu/~cmli/ % % Note 1: The original model (LBF) with a small scale parameter sigma, such as sigma = 3, is sensitive to % the initialization of the level set function. Appropriate initial level set functions are given in % this code for different test images. % Note 2: There are several ways to improve the original LBF model to make it robust to initialization. % One of the improved LBF algorithms is implemented by the code in the following link: % http://www.engr.uconn.edu/~cmli/code/LBF_v0.1.rar
程序缺乏相应的文档说明，只在演示程序中找到下面的话。应该这个代码就是实现的这个文章了。参考文献[3].
% Matlab code implementing Chan-Vese model in the paper ‘Active Contours Without Edges‘ % This method works well for bimodal images, for example the image ‘three.bmp‘
初始化时，需要画一条线。运行结果如下：
程序代码同样在第一次提到的下载连接处，Download Link，找到这个文件夹
参考文献
[1] Li C, Kao C Y, Gore J C, et al. Implicit Active Contours Driven by Local Binary Fitting Energy[C]// 2007 IEEE Conference on Computer Vision and Pattern Recognition. IEEE Computer Society, 2007:1-7.
[2] Chunming L, Chiu-Yen K, Gore J C, et al. Minimization of region-scalable fitting energy for image segmentation.[J]. IEEE Transactions on Image Processing A Publication of the IEEE Signal Processing Society, 2008, 17(10):1940-1949.
[3] Chan T F, Vese L A. Active contours without edges.[J]. IEEE Transactions on Image Processing A Publication of the IEEE Signal Processing Society, 2001, 10(2):266 - 277.
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原文地址：http://www.cnblogs.com/arxive/p/5114953.html
