种子区域生长算法停止标准

时间:2014-08-28 17:19:18

标签: matlab image-processing

我希望我的区域增长算法不考虑强度值= 1(或简单图像中的像素值= 255),我该怎么办?

我正在使用http://www.mathworks.in/matlabcentral/fileexchange/19084-region-growing/content/regiongrowing.m作为我的区域增长算法。

如果能够回答我的问题,我也可以使用其他算法。

1 个答案:

答案 0 :(得分:0)

为了回答您的问题,您应该添加以下条件:

I(xn,yn)==255 && I(xn,yn)==1
  • 我是图片
  • xn,yn是正在处理的邻居坐标

因此,当算法想要处理邻居时,它应首先考虑条件。

产生的代码

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)&&I(xn,yn)==255&&I(xn,yn)==1) 
                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;