matlab检测多个圆心_【机器视觉与图像处理】基于MATLAB+Hough的圆检测
正文之前
没错，我回来了。十天没有更新了，感觉自己都不像自己了！今天开始狂更？？？可以的！！
正文
本次文章，没有太多好写的，就是最近做的一个机器视觉的课程设计作业，是要做一个流水线的生产线建模以及对于产品的检测识别，我个人承包了圆心半径检测的内容，熬了好几天，终于找到了一个好的算法可以比较迅速准确的找到圆了。天不负我！！
这是我要检测图片，因为我们的要求是检测大小接近的图，所以我把检测半径范围规定在很小的范围内，这样的话会极大地加快速度！！所以这才是致胜的关键！！
%%%%%%%%%% main.m %%%%%%%%%%%
% 文件2 main.m
clc;
clear;
circleParaXYR=[];
I = imread('/Users/zhangzhaobo/program/MATLAB/Machine_vision/Picture/9.bmp');
%取整张图的三维尺寸
[m,n,l] = size(I);
% 通过判断对象类型来决定是否转化为灰度图
if l>1
I = rgb2gray(I);
end
%采用sobel算子来进行边缘检测
BW = edge(I,'sobel');
[m,n]=size(BW);
% 步长为1，即每次检测的时候增加的半径长度
step_r = 1;
%检测的时候每次转过的角度
step_angle = 0.1;
% 对检测的圆的大小范围预估，在实际项目中因为产品大小固定，所以可以给定较小范围，提高运行速度
minr = 508;
maxr = 510;
% 自动取最优的灰度阈值
thresh = graythresh(I);
% 调用hough_circle函数进行霍夫变换检测圆
[hough_space,hough_circle,para] = hough_circle(BW,step_r,step_angle,minr,maxr,thresh);
figure(1),imshow(I),title('原图')
figure(2),imshow(BW),title('边缘')
figure(3),imshow(hough_circle),title('检测结果')
circleParaXYR=para;
%输出
fprintf(1,'\n---------------圆统计----------------\n');
[r,c]=size(circleParaXYR); % r=size(circleParaXYR,1);
fprintf(1,' 检测出%d个圆\n',r); % 圆的个数
fprintf(1,' 圆心 半径\n'); % 圆的个数
for n=1:r
% x0=floor(circleParaXYR(n,1));
% y0=floor(circleParaXYR(n,2));
% if x0>0.25*m && x0<0.75*m && y0>0.25*n && y0<0.75*n
fprintf(1,'%d (%d，%d) %d\n',n,floor(circleParaXYR(n,1)),floor(circleParaXYR(n,2)),floor(circleParaXYR(n,3)));
% end
end
%标出圆
figure(4),imshow(I),title('检测出图中的圆')
%figure(1),imshow(I),title('检测出图中的圆')
hold on;
plot(circleParaXYR(:,2), circleParaXYR(:,1), 'r+');
for k = 1 : r %size(circleParaXYR, 1)
t=0:0.01*pi:2*pi;
x=cos(t).*circleParaXYR(k,3)+circleParaXYR(k,2);
y=sin(t).*circleParaXYR(k,3)+circleParaXYR(k,1);
plot(x,y,'r');
end
% R_max=maxr;
% acu=zeros(R_max);
% stor =[];
% for j=1:R_max
% for n=1:r
% if j == floor(circleParaXYR(n,3))
% acu(j)= acu(j)+1;
% end
% end
% stor=[stor;j,acu(j)];
% %fprintf(1,'%d,%d\n',j,acu(j));
% end
% fprintf(1,'\n------------粒子大小，数目统计---------\n');
% fprintf(1,'粒子半径，粒子个数\n');
% for j=1:R_max
% if acu(j) > 0
% fprintf(1,'%4d %8d\n',stor(j,1),stor(j,2));
% end
% end
% fprintf(1,'----------------------------------------\n');
% figure(5),plot(stor(:,1),stor(:,2),'-k','LineWidth',2),title('粒径谱');
% xlabel('粒子大小');
% ylabel('粒子个数');
% grid on;
% z=[0,10,20,30,40,50,60,70,80,90,11,35,25,42,48,40,20,75,88,94,23,10,20,30,40,78,60,76,84,95,58,10,20,30,40,50,60,70,80,90,100];%给出z的坐标
% Z=z(:);
% S=floor(abs(Z)*1);
% C=floor(abs(Z)*0.5);
% figure(6),scatter3(circleParaXYR(:,1),circleParaXYR(:,2),Z,circleParaXYR(:,3)*7,'filled'),title('构建三维粒子场');
上面是main函数，也就是最终的直接调用的函数，下面是hough_circle的m函数，在main中要调用这个函数的！
%%%%%%%%%% hough_circle.m %%%%%%%%%%%
% 文件1---hough_circle.m
function [hough_space,hough_circle,para] = hough_circle(BW,step_r,step_angle,r_min,r_max,p)
% *****************************************************
% 参数输入
% BW:二值图像；
% step_r:检测的圆半径步长
% step_angle:角度步长，单位为弧度
% r_min:最小圆半径
% r_max:最大圆半径
% p:阈值，0，1之间的数 通过调此值可以得到图中圆的圆心和半径
% *****************************************************
% 参数返回
% hough_space:参数空间，h(a,b,r)表示圆心在(a,b)半径为r的圆上的点数
% hough_circl:二值图像，检测到的圆
% para:检测到的圆的圆心、半径
circleParaXYR=[];
para=[];
[m,n] = size(BW);
size_r = round((r_max-r_min)/step_r)+1;%四舍五入
size_angle = round(2*pi/step_angle);
hough_space = zeros(m,n,size_r);
[rows,cols] = find(BW);%查找非零元素的行列坐标
ecount = size(rows);%非零坐标的个数
% Hough变换
% 将图像空间(x,y)对应到参数空间(a,b,r)
% a = x-r*cos(angle)
% b = y-r*sin(angle)
for i=1:ecount
for r=1:size_r %半径步长数
for k=1:size_angle %按一定弧度把圆几等分
a = round(rows(i)-(r_min+(r-1)*step_r)*cos(k*step_angle));
b = round(cols(i)-(r_min+(r-1)*step_r)*sin(k*step_angle));
if(a>0.35*m&a<=0.7*m&b>0.35*n&b<=0.7*n)
hough_space(a,b,r) = hough_space(a,b,r)+1;%h(a,b,r)的坐标，圆心和半径
end
end
end
end
% 搜索超过阈值的聚集点。对于多个圆的检测，阈值要设的小一点！通过调此值，可以求出所有圆的圆心和半径
max_para = max(max(max(hough_space)));%返回值就是这个矩阵的最大值
index = find(hough_space>=max_para*p);%一个矩阵中，想找到其中大于max_para*p数的位置
length = size(index);%符合阈值的个数
hough_circle = false(m,n);
%hough_circle = zeros(m,n);
%通过位置求半径和圆心。
for i=1:ecount
for k=1:length
par3 = floor(index(k)/(m*n))+1;
par2 = floor((index(k)-(par3-1)*(m*n))/m)+1;
par1 = index(k)-(par3-1)*(m*n)-(par2-1)*m;
if((rows(i)-par1)^2+(cols(i)-par2)^2
(rows(i)-par1)^2+(cols(i)-par2)^2>(r_min+(par3-1)*step_r)^2-5)
hough_circle(rows(i),cols(i)) = true; %检测的圆
end
end
end
% 从超过峰值阈值中得到
for k=1:length
par3 = floor(index(k)/(m*n))+1;%取整
par2 = floor((index(k)-(par3-1)*(m*n))/m)+1;
par1 = index(k)-(par3-1)*(m*n)-(par2-1)*m;
circleParaXYR = [circleParaXYR;par1,par2,par3];
hough_circle(par1,par2)= true; %这时得到好多圆心和半径，不同的圆的圆心处聚集好多点，这是因为所给的圆不是标准的圆
%fprintf(1,'test1:Center %d %d \n',par1,par2);
end
%集中在各个圆的圆心处的点取平均，得到针对每个圆的精确圆心和半径！
while size(circleParaXYR,1) >= 1
num=1;
XYR=[];
temp1=circleParaXYR(1,1);
temp2=circleParaXYR(1,2);
temp3=circleParaXYR(1,3);
c1=temp1;
c2=temp2;
c3=temp3;
temp3= r_min+(temp3-1)*step_r;
if size(circleParaXYR,1)>1
for k=2:size(circleParaXYR,1)
if (circleParaXYR(k,1)-temp1)^2+(circleParaXYR(k,2)-temp2)^2 > temp3^2
XYR=[XYR;circleParaXYR(k,1),circleParaXYR(k,2),circleParaXYR(k,3)]; %保存剩下圆的圆心和半径位置
else
c1=c1+circleParaXYR(k,1);
c2=c2+circleParaXYR(k,2);
c3=c3+circleParaXYR(k,3);
num=num+1;
end
end
end
%fprintf(1,'sum %d %d radius %d\n',c1,c2,r_min+(c3-1)*step_r);
c1=round(c1/num);
c2=round(c2/num);
c3=round(c3/num);
c3=r_min+(c3-1)*step_r;
%fprintf(1,'num=%d\n',num)
%fprintf(1,'Center %d %d radius %d\n',c1,c2,c3);
para=[para;c1,c2,c3]; %保存各个圆的圆心和半径的值
circleParaXYR=XYR;
end
通过上面两个函数，会有下面的结果！
Warning: Image is too big to fit on screen; displaying at 67%
> In images.internal.initSize (line 71)
In imshow (line 332)
In main (line 33)
Warning: Image is too big to fit on screen; displaying at 67%
> In images.internal.initSize (line 71)
In imshow (line 332)
In main (line 34)
Warning: Image is too big to fit on screen; displaying at 67%
> In images.internal.initSize (line 71)
In imshow (line 332)
In main (line 35)
---------------圆统计----------------
检测出1个圆
圆心 半径
1 (528，728) 509
Warning: Image is too big to fit on screen; displaying at 67%
> In images.internal.initSize (line 71)
In imshow (line 332)
In main (line 54)
>>
然后我还有另外的类似的一个，是在一本书的附赠代码里面的，因为觉得图片很美，所以也放上来吧！！
下面是代码，代码之后是原图，按照代码中的名字设置名字即可!
clear all;
close all;
i=imread('yanjing.bmp');
imshow(i);
iii=i;
%把输入图象二值化，用canny算法返回阈值
sigma=3.0;
thresh=[0.03,0.09];
bw_1=i>70;
edgerm=edge(bw_1,'canny',thresh,sigma);
figure,imshow(edgerm);
t1=280;
s=0;
while t1>10
t2=1;
while t2<310
%查找第一个边缘点
if edgerm(t1,t2)==1
u1=t1;
u2=t2;
s=1;
end
if s==1
break;
end
t2=t2+1;
end
t1=t1-1;
end
po=1;
sum2=0;
%第一个边缘点
o1=u1;
o2=u2;
hang=zeros(0,0);
lie=zeros(0,0);
while (po==1)
while (po==1)
sum1=0;
for t3=1:5
for t4=1:5
% 第一个边缘点的左上方5个像素内有边缘点
if edgerm(u1-t3+1,u2+t4-1)==1
% 第一个边缘点周围的边缘点个数
sum1=sum1+1;
sum2=sum2+1;
% 第sum1个边缘点位置x
hang(sum1,1)=u1-t3+1;
% 第sum1个边缘点位置y
hang(sum1,2)=u2+t4-1;
lie(sum2,1)=u1-t3+1;
lie(sum2,2)=u2+t4-1;
end
end
end
% 边缘点只有一个
if sum1==1
po=0;
% 没有边缘点
elseif sum1==0
po=0;
else
% 以最后的边缘点为起点，进行下一轮搜索
u1=hang(sum1,1);
u2=hang(sum1,2);
po=1;
end
end
% 边缘点个数小于30个
if sum2<30
u1=o1;
u2=o2+1;
po=1;
sum2=0;
% 横坐标不变，改变纵坐标值得到边缘点
while (edgerm(u1,u2)~=1)
while (edgerm(u1,u2)~=1)&(u2<310)
% 不是边缘点，纵坐标加1
u2=u2+1;
end
% 没有得到边缘点
if u2==310
u1=u1-1;
u2=1;
end
end
% x不变，改变y重新得到边缘点
o1=u1;
o2=u2;
else
break;
end
end
% 边缘点个数
a1=size(lie);
w1=lie(a1(1),1);
w2=lie(a1(1),2);
po1=1;
while (po1==1)
sum1=0;
for t1=1:3
for t2=1:5
% 边缘点向左方3个像素，上方5个像素
if edgerm(w1-t1+1,w2-t2+1)==1
sum1=sum1+1;
sum2=sum2+1;
lie(sum2,1)=w1-t1+1;
lie(sum2,2)=w2-t2+1;
hang(sum1,1)=w1-t1+1;
hang(sum1,2)=w2-t2+1;
end
end
end
% 边缘点只有一个
if sum1==1
po1=0;
else
po1=1;
w1=hang(sum1,1);
w2=hang(sum1,2);
end
end
po2=1;
while (po2==1)
sum1=0;
for t1=1:7
for t2=1:15
if edgerm(w1+t1-1,w2-t2+1)==1
sum1=sum1+1;
sum2=sum2+1;
lie(sum2,1)=w1+t1-1;
lie(sum2,2)=w2-t2+1;
hang(sum1,1)=w1+t1-1;
hang(sum1,2)=w2-t2+1;
end
end
end
if sum1==1
po2=0;
else
po2=1;
w1=hang(sum1,1);
w2=hang(sum1,2);
end
end
%不止一个边缘点
while (w1~=lie(1,1))&(w2~=lie(1,2))
sum1=0;
for t1=1:5
for t2=1:5
%向右向上5个像素搜索边缘点
if edgerm(w1+t1-1,w2+t2-1)==1
sum1=sum1+1;
sum2=sum2+1;
lie(sum2,1)=w1+t1-1;
lie(sum2,2)=w2+t2-1;
hang(sum1,1)=w1+t1-1;
hang(sum1,2)=w2+t2-1;
end
end
end
w1=hang(sum1,1);
w2=hang(sum1,2);
end
for t1=1:280
for t2=1:320
% 初始化Hough矩阵
e(t1,t2)=0;
end
end
% 边缘点个数
for t1=1:size(lie)
% 将是边缘点的位置设为1
e(lie(t1,1),lie(t1,2))=1;
end
%确定瞳孔的边缘的上下限
minl=320;
maxl=1;
minh=280;
maxh=1;
for t1=1:280
for t2=1:320
if (e(t1,t2)==1)&(t2
minl=t2;
end
if (e(t1,t2)==1)&(t2>maxl)
maxl=t2;
end
if (e(t1,t2)==1)&(t1
minh=t1;
end
if (e(t1,t2)==1)&(t1>maxh)
maxh=t1;
end
end
end
% 采用二值化的方法求得瞳孔的面积sum3
sum3=0;
t1=minh;
while t1<=maxh
t2=minl;
while t2<=maxl
if (bw_1(t1,t2)==0)
sum3=sum3+1;
end
t2=t2+1;
end
t1=t1+1;
end
% 得到瞳孔r1半径向上取整,sum3表示瞳孔的面积
r1=ceil(sqrt(sum3/pi));
% 向下取整 估算出瞳孔圆心x坐标
c(1,1)=floor((maxh-minh)/2+minh);
c(1,2)=ceil((maxl-minl)/2+minl);
r2=ceil(r1/3);
r3=2*r2;
for t1=1:ceil(r1/6)*2
for t2=1:ceil(r1/6)*2
pu(t1,t2)=0;
end
end
%pu中存放有相同圆心点的个数，以下找一个最大的pu认为是瞳孔的圆心
t1=minh;
while t1<=maxh
t2=minl;
while t2<=maxl
if (e(t1,t2)==1)
for a=1:2*ceil(r1/6)
for b=1:2*ceil(r1/6)
if (((t1-(c(1,1)+ceil(r1/6)-a))^2+(t2-(c(1,2)-ceil(r1/6)+b))^2-r1^2)>-10)&(((t1-(c(1,1)+ceil(r1/6)-a))^2+(t2-(c(1,2)-ceil(r1/6)+b))^2-r1^2)<10)
% 以a,b为圆心的圆累加个数
pu(a,b)=pu(a,b)+1;
end
end
end
end
t2=t2+1;
end
t1=t1+1;
end
ma=pu(1,1);
% 选取同心圆最多的圆心
for a=1:2*ceil(r1/6)
for b=1:2*ceil(r1/6)
if (ma
ma=pu(a,b);
row=a;
col=b;
end
end
end
% 圆心坐标
c(1,1)=c(1,1)+ceil(r1/6)-row;
c(1,2)=c(1,2)-ceil(r1/6)+col;
j=double(i);
for t1=1:280
for t2=1:320
%虹膜内边缘设为白色
if ((t1-c(1,1))^2+(t2-c(1,2))^2-r1^2<80)&((t1-c(1,1))^2+(t2-c(1,2))^2-r1^2>-80)
i(t1,t2)=255;
end
end
end
row1=c(1,1);
col1=c(1,2);
%以上找到圆心(row1,col1),半径r1;
ha=row1;
li=col1;
sh1=1;
zong=0;
while sh1<=3
sh2=1;
while sh2<=3
zong=zong+1;
% 圆心向左、不变、向右移动2
row1=ha-4+sh1*2;
col1=li-4+sh2*2;
j1=double(i);
u=zeros(0,0);
for t1=1:row1
t2=col1;
while t2<=310
%第一像限的图像对角变换
u(row1-t1+1,t2-col1+1)=j1(t1,t2);
t2=t2+1;
end
end
u1=double(u);
%第一像限图像的行列数
yy=size(u);
%瞳孔半径r1
rr=r1+40;
l1=r1+40;
l2=1;
ll1=0;
n1=l1;
sq1=0;
%yy(1,2)表示第一像限的矩阵列数，yy(1,1)行数
while (l2
pk=(l1-1/2)^2+(l2+1)^2-rr^2;
%半径在rr+40范围内
if pk<0
%沿着l1方向灰度值累加
sq1=sq1+u1(l2+1,l1);
%记录sql的个数
ll1=ll1+1;
l1=l1;
l2=l2+1;
else sq1=sq1+u1(l2+1,l1-1);
ll1=ll1+1;
l1=l1-1;
l2=l2+1;
end
end
%灰度平均值
sq=sq1/ll1;
for t1=r1+40:126
sr1(t1)=0;
end
rr=rr+2;
l1=n1+2;
l2=1;
while (rr<=126)&(rrl2)&(l1
n1=l1;
ll2=0;
sq2=0;
while (l1>l2)&(l1
pk=(l1-1/2)^2+(l2+1)^2-rr^2;
if pk<0
sq2=sq2+u1(l2+1,l1);
ll2=ll2+1;
l1=l1;
l2=l2+1;
else sq2=sq2+u1(l2+1,l1-1);
ll2=ll2+1;
l1=l1-1;
l2=l2-1;
end
end
sqq=sq2/ll2;
sr1(rr)=abs(sqq-sq);
sq=sqq;
rr=rr+2;
l1=n1+2;
l2=1;
end
ma1=sr1(r1+40);
t1=r1+40;
while t1<=126
if sr1(t1)>ma1
% 找出灰度值变化最大点
ma1=sr1(t1);
% 半径
rad1=t1;
end
t1=t1+1;
end
q1=zeros(0,0);
t1=row1;
while t1<280
t2=col1;
while t2<310
q1(t1-row1+1,t2-col1+1)=j1(t1,t2);
t2=t2+1;
end
t1=t1+1;
end
yy1=double(q1);
ys1=size(yy1);
rr1=r1+40;
l21=r1+40;
l22=1;
ll3=0;
n2=l21;
sq3=0;
while (l22
pk1=(l21-1/2)^2+(l22+1)^2-rr1^2;
if pk1<0
sq3=sq3+yy1(l22+1,l21);
ll3=ll3+1;
l21=l21;
l22=l22+1;
else sq3=sq3+yy1(l22+1,l21-1);
ll3=ll3+1;
l21=l21-1;
l22=l22+1;
end
end
sq=sq3/ll3;
for t1=r1+40:126
sr2(t1)=0;
end
rr1=rr1+2;
l21=n2+2;
l22=1;
while (rr1<=126)&(rr1l22)&(l21
n2=l21;
ll4=0;
sq4=0;
while (l21>l22)&(l21
pk1=(l21-1/2)^2+(l22+1)^2-rr1^2;
if pk1<0
sq4=sq4+yy1(l22+1,l21);
ll4=ll4+1;
l21=l21;
l22=l22+1;
else sq4=sq4+yy1(l22+1,l21-1);
ll4=ll4+1;
l21=l21-1;
l22=l22+1;
end
end
sqq=sq4/ll4;
sr2(rr1)=abs(sqq-sq);
sq=sqq;
rr1=rr1+2;
l21=n2+2;
l22=1;
end
ma2=sr2(r1+40);
t1=r1+40;
while t1<=126
if sr2(t1)>ma2
ma2=sr2(t1);
rad2=t1;
end
t1=t1+1;
end
%以上是第四向限
q2=zeros(0,0);
for t1=1:row1
for t2=1:col1
q2(row1+1-t1,col1+1-t2)=j1(t1,t2);
end
end
yy2=double(q2);
ys2=size(yy2);
rr2=r1+40;
l31=r1+40;
l32=1;
ll5=0;
n3=l31;
sq5=0;
while (l32
pk2=(l31-1/2)^2+(l32+1)^2-rr2^2;
if pk2<0
sq5=sq5+yy2(l32+1,l31);
ll5=ll5+1;
l31=l31;
l32=l32+1;
else sq5=sq5+yy2(l32+1,l31-1);
ll5=ll5+1;
l31=l31-1;
l32=l32+1;
end
end
sq=sq5/ll5;
for t1=r1+40:126
sr3(t1)=0;
end
rr2=rr2+2;
l31=n3+2;
l32=1;
while (rr2<=126)&(rr2l32)&(l31
n3=l31;
ll6=0;
sq6=0;
while (l31>l32)&(l31
pk2=(l31-1/2)^2+(l32+1)^2-rr2^2;
if pk2<0
sq6=sq6+yy2(l32+1,l31);
ll6=ll6+1;
l31=l31;
l32=l32+1;
else sq6=sq6+yy2(l32+1,l31-1);
ll6=ll6+1;
l31=l31-1;
l32=l32+1;
end
end
sqq=sq6/ll6;
sr3(rr2)=abs(sqq-sq);
sq=sqq;
rr2=rr2+2;
l31=n3+2;
l32=1;
end
ma3=sr3(r1+40);
t1=r1+40;
while t1<=126
if sr3(t1)>ma3
ma3=sr3(t1);
rad3=t1;
end
t1=t1+1;
end
%以上是第二向限
j1=double(i);
q3=zeros(0,0);
t1=row1;
while t1<280
for t2=1:col1
q3(t1-row1+1,col1+1-t2)=j1(t1,t2);
end
t1=t1+1;
end
yy3=double(q3);
ys3=size(yy3);
rr3=r1+40;
l41=r1+40;
l42=1;
ll7=0;
n4=l41;
sq7=0;
while (l42
pk3=(l41-1/2)^2+(l42+1)^2-rr3^2;
if pk3<0
sq7=sq7+yy3(l42+1,l41);
ll7=ll7+1;
l41=l41;
l42=l42+1;
else sq7=sq7+yy3(l42+1,l41-1);
ll7=ll7+1;
l41=l41-1;
l42=l42+1;
end
end
sq=sq7/ll7;
for t1=r1+40:126
sr4(t1)=0;
end
rr3=rr3+2;
l41=n4+2;
l42=1;
while (rr3<=126)&(rr3l42)&(l41
n4=l41;
ll8=0;
sq8=0;
while (l41>l42)&(l41
pk3=(l41-1/2)^2+(l42+1)^2-rr3^2;
if pk3<0
sq8=sq8+yy3(l42+1,l41);
ll8=ll8+1;
l41=l41;
l42=l42+1;
else sq8=sq8+yy3(l42+1,l41-1);
ll8=ll8+1;
l41=l41-1;
l42=l42+1;
end
end
sqq=sq8/ll8;
sr4(rr3)=abs(sqq-sq);
sq=sqq;
rr3=rr3+2;
l41=n4+2;
l42=1;
end
ma4=sr4(r1+40);
t1=r1+40;
while t1<=126
if sr4(t1)>ma4
ma4=sr4(t1);
rad4=t1;
end
t1=t1+1;
end
% 以上是第三向限
% 四个像限的半径平均值
ra(zong)=(rad1+rad2+rad3+rad4)/4;
% 圆心位置
xin(zong,1)=row1;
xin(zong,2)=col1;
sh2=sh2+1;
% 4个像限最大灰度差值和
ma(zong)=ma1+ma2+ma3+ma4;
end
sh1=sh1+1;
end
max1=ma(1);
for t1=1:zong
if max1<=ma(t1)
% 最大值是第t1次循环
shh=t1;
% 循环后的最大灰度差值
max1=ma(t1);
end
end
jing=0;
for t1=1:zong
jing=jing+ra(t1);
end
% 虹膜半径
jing=floor(jing/zong);
% 虹膜的圆心
row2=xin(shh,1);
col2=xin(shh,2);
for t1=1:280
for t2=1:320
if ((t1-row2-2)^2+(t2-col2+4)^2-jing^2<200)&((t1-row2-2)^2+(t2-col2+4)^2-jing^2>-200)
%设置虹膜外边缘为白色
i(t1,t2)=255;
end
end
end
for t1=1:280
for t2=1:320
if ((t1-c(1,1))^2+(t2-c(1,2))^2<=r1^2)|((t1-c(1,1))^2+(t2-c(1,2))^2>=jing^2)
%把虹膜以外的部分设为白色
iii(t1,t2)=255;
end
end
end
figure,imshow(i);
figure,imshow(iii);
yanjing.bmp
正文之后
没错，我回来了，再次宣布！！！溜了溜了。大后天就开始考研了，我把房子借给好朋友的青梅竹马但是不是女朋友的考研人了！所以明天出去住宾馆去~~ 权当是旅游咯！！