function ret=growseed()

%=====区域生长算法========

%input :二值图像数据

%output:边界点二值图像数据

global I;global M;

global N;global Y;global T;global newy;global newx;%==边界点x,y坐标

%获取多张图片的二值数据

tempI=draw(); %tempI 36*45*numbertotal

count=length(tempI(1,1,:));

wide=length(tempI(:,1,1));%36

high=length(tempI(1,:,1));%45

result=zeros(wide,high,count);

for k=1:count

I=tempI(:,:,k);

% figure,imshow(I),title('原始图像')

I=double(I);

[M,N]=size(I);

[seedx,seedy]=searchseed(I);

Y=zeros(M,N); %作一个全零与原图像等大的图像矩阵Y，作为输出图像矩阵

T=zeros(M,N);%标记点。。。

newx=0;newy=0;

calseed(seedx,seedy);

figure,imshow(Y);

% if k>1&&k

% result(:,:,k)=Y;

% figure,imshow(Y);

% else

% result(:,:,k)=T;

% % imshow(T);

% % figure,imshow(T);

% end

end

ret=result;

end

function calseed(seedx,seedy)

global M;

global N;

global Y;

global I;

global newx;

global newy;

global T;

for i = -1 : 1

for j = -1 : 1

newseedx = seedx + i;

newseedy = seedy+ j;

%生长准则：判断生长点8邻域内像素的各自灰度值是否与生长点所在像素灰度值相等

if newseedx> 0 && newseedx <= M && newseedy > 0 && newseedy <= N &&T(newseedx,newseedy)==0&&I(newseedx,newseedy)==1

T(newseedx,newseedy)=1;

if isequal(newseedx,newseedy)==1

calseed(newseedx,newseedy);

else

Y(newx,newy)=1;%set边界点值为1

end

end

end

end

end

function ret=isequal(x,y)%====判断点的领域是否相等

%===输入1个点的x,y坐标

%==返回1 相等

global I;

global newx;

global newy;

global M;

global N;

ret=1;

tag=0;

for i = -1 : 1

if tag==0

for j = -1 : 1

if x+i> 0 && x+i <= M && y+j > 0 && y+j <= N

if I( x+i,y+j)==0

ret=0;

tag=1;

newx=x+i;

newy=y+j;

end

end

end

end

end

end

function [x,y]=searchseed(I)

%=========寻找种子点=====

%Input:一张二值数据的图片

%Output:返回种子点的x,y坐标

%======求数据为1的质心====

[M,N]=size(I);

corx=0;

cory=0;

count=0;

for i=1:M

for j=1:N

if I(i,j)==1

corx=corx+i;

cory=cory+j;

count=count+1;

end

end

end

x=round(corx/count);

y=round(cory/count);

end

处理结果