clear ;
close all;
%Step1 Get images Load the color image to be processed and display the original image
Scolor = imread('3.jpg');%imread Function to read the image file
% Convert color images to black and white and display
Sgray = rgb2gray(Scolor);%rgb2gray Convert to grayscale
figure,imshow(Scolor),title(' Original color image ');%figure Command to display two images at the same time
figure,imshow(Sgray),title(' Original black and white image ');
%Step2 Image preprocessing Yes Sgray The original black-and-white image is opened to obtain the image background
s=strel('disk',13);%strei function
Bgray=imopen(Sgray,s);% open sgray s Images
figure,imshow(Bgray);title(' background image ');% Output background image
% Subtract the original image from the background image , Enhance the image
Egray=imsubtract(Sgray,Bgray);% Subtract the two pictures
figure,imshow(Egray);title(' Enhance black and white images ');% Output black and white images
%Step3 Get the best threshold , Binarize the image
fmax1=double(max(max(Egray)));%egray And output double precision
fmin1=double(min(min(Egray)));%egray And output double precision
level=(fmax1-(fmax1-fmin1)/3)/255;% Get the best threshold
bw22=im2bw(Egray,level);% Convert image to binary image
bw2=double(bw22);
%Step4 The binary image is filtered by opening and closing operation
figure,imshow(bw2);title(' Image binarization ');% Get a binary image
grd=edge(bw2,'canny')% use canny The operator recognizes the boundary in the intensity image
figure,imshow(grd);title(' Image edge extraction ');% Output image edge
bg1=imclose(grd,strel('rectangle',[5,19]));% Take the closed operation of the rectangular box
figure,imshow(bg1);title(' Image closed operation [5,19]');% Output the image of closed operation
bg3=imopen(bg1,strel('rectangle',[5,19]));% Open operation of rectangular box
figure,imshow(bg3);title(' Image open operation [5,19]');% Output the image of open operation
bg2=imopen(bg3,strel('rectangle',[19,1]));% Open operation of rectangular box
figure,imshow(bg2);title(' Image open operation [19,1]');% Output the image of open operation
%Step5 Region extraction of binary image , And calculate the regional characteristic parameters . Compare the regional characteristic parameters , Extract the license plate area
[L,num] = bwlabel(bg2,8);% Label the connected part of the binary image
Feastats = regionprops(L,'basic');% Calculate the feature size of the image area
Area=[Feastats.Area];% Area
BoundingBox=[Feastats.BoundingBox];%[x y width height] The frame size of the license plate
RGB = label2rgb(L, 'spring', 'k', 'shuffle'); % Logo image to RGB Image conversion
figure,imshow(RGB);title(' Image color marking ');% Output the color image of the frame
lx=0;
for l=1:num
width=BoundingBox((l-1)*4+3);% Calculation of frame width
hight=BoundingBox((l-1)*4+4);% Calculation of frame height
if (width>98 & width<160 & hight>25 & hight<50)% The width and height of the frame
lx=lx+1;
Getok(lx)=l;
end
end
for k= 1:lx
l=Getok(k);
startcol=BoundingBox((l-1)*4+1)-2;% Start the column
startrow=BoundingBox((l-1)*4+2)-2;% Go ahead
width=BoundingBox((l-1)*4+3)+8;% The license plate is wide
hight=BoundingBox((l-1)*4+4)+2;% License plate height
rato=width/hight;% Calculate the aspect ratio of the license plate
if rato>2 & rato<4
break;
end
end
sbw1=bw2(startrow:startrow+hight,startcol:startcol+width-1); % Get the binary subgraph of the license plate
subcol1=Sgray(startrow:startrow+hight,startcol:startcol+width-1);% Obtain the gray sub image of the license plate
figure,subplot(2,1,1),imshow(subcol1);title(' Gray level subgraph of license plate ');% Output grayscale image
subplot(2,1,2),imshow(sbw1);title(' License plate binary subgraph ');% Output the binary diagram of the license plate
%Step6 Calculate the horizontal projection of the license plate , The peak valley analysis of horizontal projection
histcol1=sum(sbw1); % Calculate the vertical projection
histrow=sum(sbw1'); % Calculate the horizontal projection
figure,subplot(2,1,1),bar(histcol1);title(' Vertical projection （ With border ）');% Output vertical projection
subplot(2,1,2),bar(histrow); title(' Horizontal projection （ With border ）');% Output horizontal projection
figure,subplot(2,1,1),bar(histrow); title(' Horizontal projection （ With border ）');% Output horizontal projection
subplot(2,1,2),imshow(sbw1);title(' License plate binary subgraph ');% Output binary graph
% Peak valley analysis of horizontal projection
meanrow=mean(histrow);% Find the average of the horizontal projection
minrow=min(histrow);% Find the minimum value of horizontal projection
levelrow=(meanrow+minrow)/2;% Find the average of the horizontal projection
count1=0;
l=1;
for k=1:hight
if histrow(k)<=levelrow
count1=count1+1;
else
if count1>=1
markrow(l)=k;% Rising point
markrow1(l)=count1;% Valley width （ From the falling point to the next rising point ）
l=l+1;
end
count1=0;
end
end
markrow2=diff(markrow);% Peak distance （ Rising point to the next rising point ）
[m1,n1]=size(markrow2);
n1=n1+1;
markrow(l)=hight;
markrow1(l)=count1;
markrow2(n1)=markrow(l)-markrow(l-1);
l=0;
for k=1:n1
markrow3(k)=markrow(k+1)-markrow1(k+1);% Drop point
markrow4(k)=markrow3(k)-markrow(k);% Peak width （ Rising point to falling point ）
markrow5(k)=markrow3(k)-double(uint16(markrow4(k)/2));% Peak center position
end
%Step7 Calculate the license plate rotation angle
%(1) Find the first one from the rising point to the falling point as 1 The point of
[m2,n2]=size(sbw1);%sbw1 The image size of
[m1,n1]=size(markrow4);%markrow4 Size
maxw=max(markrow4);% The maximum width is characters
if markrow4(1) ~= maxw% Check the upper
ysite=1;
k1=1;
for l=1:n2
for k=1:markrow3(ysite)% Scan from the top edge to the falling point of the first peak
if sbw1(k,l)==1
xdata(k1)=l;
ydata(k1)=k;
k1=k1+1;
break;
end
end
end
else % Check the bottom
ysite=n1;
if markrow4(n1) ==0
if markrow4(n1-1) ==maxw
ysite= 0; % No bottom
else
ysite= n1-1;
end
end
if ysite ~=0
k1=1;
for l=1:n2
k=m2;
while k>=markrow(ysite) % Scan from the bottom to the rising point of the last peak
if sbw1(k,l)==1
xdata(k1)=l;
ydata(k1)=k;
k1=k1+1;
break;
end
k=k-1;
end
end
end
end
%(2) Linear fitting , Calculation and x Angle
fresult = fit(xdata',ydata','poly1'); %poly1 Y = p1*x+p2
p1=fresult.p1;
angle=atan(fresult.p1)*180/pi; % Change radians into degrees ,360/2pi, pi=3.14
%(3) Rotate the license plate image
subcol = imrotate(subcol1,angle,'bilinear','crop'); % Rotate the license plate image
sbw = imrotate(sbw1,angle,'bilinear','crop');% Rotated image
figure,subplot(2,1,1),imshow(subcol);title(' Gray level subgraph of license plate ');% Output the gray image title after license plate rotation, and display the gray sub image of license plate
subplot(2,1,2),imshow(sbw);title('');% Output the gray image of the license plate after rotation
title([' License plate rotation angle : ',num2str(angle),' degree '] ,'Color','r');% Display the rotation angle of the license plate
%Step8 After rotating the license plate, recalculate the horizontal projection of the license plate , Remove the horizontal border of the license plate , Gets the character height
histcol1=sum(sbw); % Calculate the vertical projection
histrow=sum(sbw'); % Calculate the horizontal projection
figure,subplot(2,1,1),bar(histcol1);title(' Vertical projection （ After rotation ）');
subplot(2,1,2),bar(histrow); title(' Horizontal projection （ After rotation ）');
figure,subplot(2,1,1),bar(histrow); title(' Horizontal projection （ After rotation ）');
subplot(2,1,2),imshow(sbw);title(' License plate binary subgraph （ After rotation ）');
% Go to the level （ Up and down ） Frame , Gets the character height
maxhight=max(markrow2);
findc=find(markrow2==maxhight);
rowtop=markrow(findc);
rowbot=markrow(findc+1)-markrow1(findc+1);
sbw2=sbw(rowtop:rowbot,:); % The subgraph is (rowbot-rowtop+1) That's ok
maxhight=rowbot-rowtop+1; % character height (rowbot-rowtop+1)
%Step9 Calculate the vertical projection of the license plate , Remove the vertical border of the license plate , Get the average width of license plate and characters
histcol=sum(sbw2); % Calculate the vertical projection
figure,subplot(2,1,1),bar(histcol);title(' Vertical projection （ After removing the horizontal border ）');% Output the vertical projection image of the license plate
subplot(2,1,2),imshow(sbw2); % Output vertical projection image
title([' License plate character height ： ',int2str(maxhight)],'Color','r');% Output license plate character height
% Peak valley analysis of vertical projection
meancol=mean(histcol);% Find the average of the vertical projection
mincol=min(histcol);% Find the average of the vertical projection
levelcol=(meancol+mincol)/4;% Find the of vertical projection 1/4
count1=0;
l=1;
for k=1:width
if histcol(k)<=levelcol
count1=count1+1;
else
if count1>=1
markcol(l)=k; % Character rising point
markcol1(l)=count1; % Valley width （ From the falling point to the next rising point ）
l=l+1;
end
count1=0;
end
end


1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
11.
12.
13.
14.
15.
16.
17.
18.
19.
20.
21.
22.
23.
24.
25.
26.
27.
28.
29.
30.
31.
32.
33.
34.
35.
36.
37.
38.
39.
40.
41.
42.
43.
44.
45.
46.
47.
48.
49.
50.
51.
52.
53.
54.
55.
56.
57.
58.
59.
60.
61.
62.
63.
64.
65.
66.
67.
68.
69.
70.
71.
72.
73.
74.
75.
76.
77.
78.
79.
80.
81.
82.
83.
84.
85.
86.
87.
88.
89.
90.
91.
92.
93.
94.
95.
96.
97.
98.
99.
100.
101.
102.
103.
104.
105.
106.
107.
108.
109.
110.
111.
112.
113.
114.
115.
116.
117.
118.
119.
120.
121.
122.
123.
124.
125.
126.
127.
128.
129.
130.
131.
132.
133.
134.
135.
136.
137.
138.
139.
140.
141.
142.
143.
144.
145.
146.
147.
148.
149.
150.
151.
152.
153.
154.
155.
156.
157.
158.
159.
160.
161.
162.
163.
164.
165.
166.
167.
168.
169.
170.
171.
172.
173.
174.
175.
176.
177.
178.
179.
180.
181.
182.
183.
184.
185.
186.
187.
188.
189.
190.