NarrowBand_DLL.rar_S-BAND_level set_narrow band _narrowband_dll.

% This Matlab file demomstrates a narrow band algorithm that implements the level set method in Li et al's paper % "Level Set Evolution Without Re-initialization: A New Variational Formulation" % in Proceedings of CVPR'05, vol. 1, pp. 430-436. % Author: Chunming Li, all rights reserved. % E-mail: li_chunming@hotmail.com % URL: http://222.178.203.72:19005/whst/63/_vvvzdmfqztbnmmzdct//~cmli/ clear all; close all; Img = imread('twoObjImg.bmp'); Img=double(Img(:,:,1)); sigma=1.5; % scale parameter in Gaussian kernel for smoothing. [nrow, ncol]=size(Img); total_time = 0; G=fspecial('gaussian',15,sigma); Img_smooth=conv2(Img,G,'same'); % smooth image by Gaussiin convolution [Ix,Iy]=gradient(Img_smooth); f=Ix.^2+Iy.^2; g=1./(1+f); % edge indicator function. [vx,vy] = gradient(g); tic; total_time = total_time + toc; epsilon=1.5; % the papramater in the definition of smoothed Dirac function N_iter=150; timestep=5; % time step mu=0.04; % coefficient of the internal (penalizing) energy term P(\phi) % Note: The product timestep*mu must be less than 0.25 for stable evolution DiracSigma=1.5; % the papramater in the definition of smoothed Dirac function lambda=5; % coefficient of the weighted length term Lg(\phi) alf=3; % coefficient of the weighted area term Ag(\phi); % Note: Choose a positive(negative) alf if the initial contour is outside(inside) the object. d = 1; % specify the width of the narrow band. The narrow band is % the union of (2d+1)x(2d+1) blocks centered at the zero crossing pixels. % Note: don't change this parameter for this version (nband_v14). epsilon = .000001; % small positive number added to the denominator to avoid 0 in the denominator rad = d; vs=d+1; figure;imagesc(Img, [0, 255]);colormap(gray);hold on; text(6,6,'Left click to get points, right click to get end point','FontSize',[12],'Color', 'r'); % Use mouse to obtain initial contour/region; BW = roipoly; % get a region R inside a polygon, BW is a binary image with 1 and 0 inside or outside the polygon; c0=2; % The constant value used to define binary level set function as initial LSF; % Using larger value of c0 usually slows down the evolution. initialLSF= c0*2*(0.5-BW); % initial level set function: -c0 inside R, c0 outside R; u=initialLSF; figure;imagesc(Img, [0, 255]);colormap(gray);hold on; [c,h] = contour(u,[0 0],'b'); title('Initial contour'); %initial bandmap, bandMap = initializeNB(u); total_iter_time = 0; ops{1}.name = 'normalGradient'; ops{end+1}.name = 'Dirac'; ops{end+1}.name = 'curvature'; ops{end+1}.name = 'computeDataTerm'; ops{end+1}.name = 'updateLSF'; ops{end+1}.name = 'updateZeroCrossBand'; ops{end+1}.name = 'updateZCBand init'; ops{end+1}.name = 'total time'; total_stats = zeros(length(ops), 1); tic; t1=cputime; [u, bandMap, ux, uy, Nx, Ny, diracU, K, ABD, f, E,Stats] = ... nband_v14(u, bandMap, DiracSigma, vs, lambda, alf, mu, timestep, rad, vx, vy, g, nrow, ncol, N_iter); t2=cputime; iterationTime=t2-t1 total_stats = total_stats + Stats; total_iter_time = total_iter_time + toc; total_time = total_time + total_iter_time; %hold on; figure;imagesc(Img, [0, 255]);colormap(gray);hold on; [c,h] = contour(u,[0 0],'r'); iterNum=[num2str(N_iter), ' iterations']; title(iterNum); disp(' '); printStats(ops, total_stats); disp(' '); % display statistics of CPU times disp(' =============== time statistics (Matlab) ================'); disp(sprintf('%26s\t %.6g s', 'total iteration time', total_iter_time)); disp(sprintf('%26s\t %.6g s', 'total time (init/iter)', total_time)); disp(' ');