- 前言
①经过在工厂的实地测试，图像采集与传输装置可以正常工作，电脑端可以接收到清晰的图像，并且整个系统具有一定的的抗干扰的能力，在嘈杂的环境中亦可以实现其功能。
②通过matlab可实现图片的预处理以及指针识别读数识别，读取的数据相对准确
③通过labview可以成功的调用matlab函数，并实现函数的功能，通过labview搭建的界面，可以观测到实时的仪表读数以及仪表图像，可以观测到仪表读数在一段时间内的变化情况，并且可以实现连续的运行。
④整个系统的稳定性较高，可以实现持续的工作，对所处理的仪表图像的适应性较强。
在本次设计中，我学习了matlab，labview程序设计以及access的相关知识，学习了图像处理的相关方法，学会了更多解决问题、处理问题的方法，增强了处理问题的能力，为今后的发展奠定了良好的基础。
2、效果图
3、核心程序
clear;
clc;
close all;
RGB=imread('1.jpg');
figure,imshow(RGB); title('RGB')
GRAY=rgb2gray(RGB);
figure,imshow(GRAY); title('GRAY')
threshold=graythresh(GRAY);
BW=im2bw(GRAY,threshold);
figure,imshow(BW); title('BW')
BW=~BW;
figure,imshow(BW); title('~BW')
BW=bwmorph(BW,'thin',Inf);
figure,imshow(BW); title('BWMORPH')
[M,N]=size(BW);
[H,T,R] = hough(BW);
figure;
plot(xy_long(:,1),xy_long(:,2),'LineWidth',2,'Color','cyan');
k=(xy(2,2)-xy(1,2))/(xy(2,1)-xy(1,1));
theta=pi/2+atan(k);
if((xy(1,1)+xy(2,1))/2<=N/2)
q=(theta+pi)*180/3.14;
else
q=theta*180/3.14;
end
shishu=q*6/2700-0.2;
disp (theta);
disp (q);
disp (shishu);
j=imread('1.jpg');
x=RGB2gray(j);
subplot(1,2,1);
imshow(x);
title('原图像');
f=double(x);
[m,n]=size(f);
h=fspecial('gaussian',[25,25],80);%创建高斯模板
q=imfilter(f,h,'same');
s=log(f+0.03)-log(q+0.03);
r=exp(s);
%归一化处理
max_r=max(r(:))*0.27;
min_r=min(r(:));
r=(r-min_r)/(max_r-min_r);
index=find(r>1);
r(index)=1;
R=mat2gray(r);
subplot(1,2,2);
imshow(R);
title('处理后的图像');
G=im2bw(R,0.7);
imshow(G);
I=uint8(G);
bw=edge(I,'sobel');
imshow(bw);
A=imread('1.jpg');
I=rgb2gray(A);
T=0.5*(double(min(I(:)))+double(max(I(:))));
done=false;
while ~done
g=I>=T;
Tnext=0.5*(mean(I(g))+mean(I(~g)));
done=abs(T-Tnext)<0.5;
T=Tnext;
end
J=I;
K=find(J>=T);
J(K)=255;
K=find(J<T);
J(K)=0;
figure;
subplot(1,2,1),imshow(I,[]),title('原始图像');
subplot(1,2,2),imshow(J,[]),title('分割后图像');
t1=clock;
I=imread('1.jpg');
subplot(1,2,1);
J=rgb2gray(I);
title('pso算法图像分割的结果');
[a,b]=size(J);
[p,x]=imhist(J,256);
L=x';
LP=p'/(a*b);
n=256;
c1=2;
c2=2;
wmax=0.9;
wmin=0.4;
G=10;
M=15;
X=min(L)+fix((max(L)-min(L))*rand(1,M));
V=min(L)+(max(L)-min(L))*rand(1,M);
m=0;
for i=1:1:n
m=m+L(i)*LP(i);
endpbest=zeros(M,2);
gbest1=0;
gbest2=0;
GG=0;
t2=clock;
for k=1:1:G
w(k)=wmax-(wmax-wmin)*k/G;
for i=1:1:M
t=length(find(X(i)>=L));
r=0;
s=0;
for j=1:1:t
r=r+LP(j);
s=s+L(j)*LP(j);
end
W0(i)=r;
W1(i)=1-r;
U0(i)=s/r;
U1(i)=(m-s)/(1-r);
end
for i0=1:1:M
BB(i0)=W0(i0)*W1(i0)*((U1(i0)-U0(i0))^2);
end
for i=1:1:M
if pbest(i,2)<BB(i)
pbest(i,2)=BB(i);
pbest(i,1)=X(i);
end
end
[MAX,CC]=max(BB);
if MAX>=gbest2
gbest2=MAX;
gbest1=X(CC);
end
GG(k)=gbest2;
for i=1:1:M
V(i)=round(w(k)*V(i)+c1*rand*(pbest(i,1)-X(i))+c2*rand*(gbest1-X(i)));
X(i)=V(i)+X(i);
end
end
for i=1:1:a
for j=1:1:b
if J(i,j)>gbest1
J(i,j)=250;
else
J(i,j)=0;
end
end
end
kk=1:1:G;
gbest1;
figure(1);
imshow(J);
figure(2);
plot(kk,GG)
tt=etime(clock,t1);
end
I=imread('1.jpg');
tmin=min(I(:));
tmax=max(I(:));
th=(tmin+tmax)/2;
ok=true;
while ok
g1=I>=th;
g2=I<th;
u1=mean(I(g1));
u2=mean(I(g2));
tnew=(u1+u2)/2;
if abs(th-tnew)<1
ok=0;
end
end
th=tnew;
th=floor(th);
Inew=im2bw(I,th/255);
subplot(1,2,1)
imshow(I);
title('原始图像');
subplot(1,2,2)
imshow(Inew);
t=['迭代法分割后的图像，阈值=' num2str(th)];
title(t);
A0=imread('1.jpg');
seed=[100,220];
thresh=15;%相似性选择阈值
A=rgb2gray(A0);
A=imadjust(A,[min(min(double(A)))/255,max(max(double(A)))/255],[]);
A=double(A);
B=A;
[r,c]=size(B);
n=r*c;
pixel_seed=A(seed(1),seed(2));
q=[seed(1) seed(2)];
top=1;
M=zeros(r,c);
M(seed(1),seed(2))=1;
count=1;
while top~=0;
r1=q(1,1);
c1=q(1,2);
p=A(r1,c1);
dge=0;
for i=-1:1
for j=-1:1
if r1+i<=r & r1+i>0 & c1+j<=c & c1+j>0
if abs(A(r1+i,c1+j)-p)<=thresh & M(r1+i,c1+j)~=1
top=top+1;
q(top,:)=[r1+i c1+j];
M(r1+i,c1+j)=1;
count=count+1;
B(r1+i,c1+j)=1;
end
if M(r1+i,c1+j)==0;
dge=1;
end
else
dge=1;
end
end
end
if dge~=1
B(r1,c1)=A(seed(1),seed(2));
end
if count>=n
top=1;
end
q=q(2:top,:);
top=top-1;
end
subplot(1,2,1),imshow(A,[]);
subplot(1,2,2),imshow(B,[]);
A0=imread('1.jpg');
seed=[100,220];
thresh=15;%相似性选择阈值
A=rgb2gray(A0);
A=imadjust(A,[min(min(double(A)))/255,max(max(double(A)))/255],[]);
A=double(A);
B=A;
[r,c]=size(B);
n=r*c;
pixel_seed=A(seed(1),seed(2));
q=[seed(1) seed(2)];
top=1;
M=zeros(r,c);
M(seed(1),seed(2))=1;
count=1;
while top~=0;
r1=q(1,1);
c1=q(1,2);
p=A(r1,c1);
dge=0;
for i=-1:1
for j=-1:1
if r1+i<=r & r1+i>0 & c1+j<=c & c1+j>0
if abs(A(r1+i,c1+j)-p)<=thresh & M(r1+i,c1+j)~=1
top=top+1;
q(top,:)=[r1+i c1+j];
M(r1+i,c1+j)=1;
count=count+1;
B(r1+i,c1+j)=1;
end
if M(r1+i,c1+j)==0;
dge=1;
end
else
dge=1;
end
end
end
if dge~=1
B(r1,c1)=A(seed(1),seed(2));
end
if count>=n
top=1;
end
q=q(2:top,:);
top=top-1;
end
subplot(1,2,1),imshow(A,[]);
subplot(1,2,2),imshow(B,[]);
A0=imread('1.jpg');
seed=[100,220];
thresh=15;%相似性选择阈值
A=rgb2gray(A0);
A=imadjust(A,[min(min(double(A)))/255,max(max(double(A)))/255],[]);
A=double(A);
B=A;
[r,c]=size(B);
n=r*c;
pixel_seed=A(seed(1),seed(2));
q=[seed(1) seed(2)];
top=1;
M=zeros(r,c);
M(seed(1),seed(2))=1;
count=1;
while top~=0;
r1=q(1,1);
c1=q(1,2);
p=A(r1,c1);
dge=0;
for i=-1:1
for j=-1:1
if r1+i<=r & r1+i>0 & c1+j<=c & c1+j>0
if abs(A(r1+i,c1+j)-p)<=thresh & M(r1+i,c1+j)~=1
top=top+1;
q(top,:)=[r1+i c1+j];
M(r1+i,c1+j)=1;
count=count+1;
B(r1+i,c1+j)=1;
end
if M(r1+i,c1+j)==0;
dge=1;
end
else
dge=1;
end
end
end
if dge~=1
B(r1,c1)=A(seed(1),seed(2));
end
if count>=n
top=1;
end
q=q(2:top,:);
top=top-1;
end
subplot(1,2,1),imshow(A,[]);
subplot(1,2,2),imshow(B,[]);
A0=imread('1.jpg');
seed=[100,220];
thresh=15;%相似性选择阈值
A=rgb2gray(A0);
A=imadjust(A,[min(min(double(A)))/255,max(max(double(A)))/255],[]);
A=double(A);
B=A;
[r,c]=size(B);
n=r*c;
pixel_seed=A(seed(1),seed(2));
q=[seed(1) seed(2)];
top=1;
M=zeros(r,c);
M(seed(1),seed(2))=1;
count=1;
while top~=0;
r1=q(1,1);
c1=q(1,2);
p=A(r1,c1);
dge=0;
for i=-1:1
for j=-1:1
if r1+i<=r & r1+i>0 & c1+j<=c & c1+j>0
if abs(A(r1+i,c1+j)-p)<=thresh & M(r1+i,c1+j)~=1
top=top+1;
q(top,:)=[r1+i c1+j];
M(r1+i,c1+j)=1;
count=count+1;
B(r1+i,c1+j)=1;
end
if M(r1+i,c1+j)==0;
dge=1;
end
else
dge=1;
end
end
end
if dge~=1
B(r1,c1)=A(seed(1),seed(2));
end
if count>=n
top=1;
end
q=q(2:top,:);
top=top-1;
end
subplot(1,2,1),imshow(A,[]);
subplot(1,2,2),imshow(B,[]);
