区域生长算法的MATLAB编程实现

function J=regiongrowing(I,x,y,reg_maxdist) % This function performs "region growing" in an image from a specified % seedpoint (x,y) % % J = regiongrowing(I,x,y,t) % % I : input image % J : logical output image of region % x,y : the position of the seedpoint (if not given uses function getpts) % t : maximum intensity distance (defaults to 0.2) % % The region is iteratively grown by comparing all unallocated neighbouring pixels to the region. % The difference between a pixel's intensity value and the region's mean, % is used as a measure of similarity. The pixel with the smallest difference % measured this way is allocated to the respective region. % This process stops when the intensity difference between region mean and % new pixel become larger than a certain treshold (t) % % Example: % % I = im2double(imread('medtest.png')); % x=198; y=359; % J = regiongrowing(I,x,y,0.2); % figure, imshow(I+J); % % Author: D. Kroon, University of Twente if(exist('reg_maxdist','var')==0), reg_maxdist=0.2; end if(exist('y','var')==0), figure, imshow(I,[]); [y,x]=getpts; y=round(y(1)); x=round(x(1)); end J = zeros(size(I)); % Output Isizes = size(I); % Dimensions of input image reg_mean = I(x,y); % The mean of the segmented region reg_size = 1; % Number of pixels in region % Free memory to store neighbours of the (segmented) region neg_free = 10000; neg_pos=0; neg_list = zeros(neg_free,3); pixdist=0; % Distance of the region newest pixel to the regio mean % Neighbor locations (footprint) neigb=[-1 0; 1 0; 0 -1;0 1]; % Start regiogrowing until distance between regio and posible new pixels become % higher than a certain treshold while(pixdist<reg_maxdist&&reg_size<numel(I)) % Add new neighbors pixels for j=1:4, % Calculate the neighbour coordinate xn = x +neigb(j,1); yn = y +neigb(j,2); % Check if neighbour is inside or outside the image ins=(xn>=1)&&(yn>=1)&&(xn<=Isizes(1))&&(yn<=Isizes(2)); % Add neighbor if inside and not already part of the segmented area if(ins&&(J(xn,yn)==0)) neg_pos = neg_pos+1; neg_list(neg_pos,:) = [xn yn I(xn,yn)]; J(xn,yn)=1; end end % Add a new block of free memory if(neg_pos+10>neg_free), neg_free=neg_free+10000; neg_list((neg_pos+1):neg_free,:)=0; end % Add pixel with intensity nearest to the mean of the region, to the region dist = abs(neg_list(1:neg_pos,3)-reg_mean); [pixdist, index] = min(dist); J(x,y)=2; reg_size=reg_size+1; % Calculate the new mean of the region reg_mean= (reg_mean*reg_size + neg_list(index,3))/(reg_size+1); % Save the x and y coordinates of the pixel (for the neighbour add proccess) x = neg_list(index,1); y = neg_list(index,2); % Remove the pixel from the neighbour (check) list neg_list(index,:)=neg_list(neg_pos,:); neg_pos=neg_pos-1; end % Return the segmented area as logical matrix J=J>1;