一、简介
模型参考这里。
二、源代码
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% resize的目标尺寸650*X
% 调参
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
clear;
se1 = strel('rectangle',[15 15]); %创建一个平坦的矩形结构
se2 = strel('rectangle',[12 20]); %创建一个平坦的矩形结构
se3 = strel('rectangle',[12 15]);
imgraw=imread('C:\Users\lenovo\Desktop\licenseplate\0.png'); %读取图
% se1 = strel('rectangle',[15 25]); %创建一个平坦的矩形结构
% se2 = strel('rectangle',[10 25]); %创建一个平坦的矩形结构
% se3 = strel('rectangle',[14 19]);
% imgraw=imread('E:\matlab workspace\licenseplate\车牌2.jpg'); %读取图像
[m,~]=size(imgraw);
times = 650/m;
img=imresize(imgraw,times,'nearest');
g= fspecial('gaussian',[5,5],1); %高斯滤波器
g_img = imfilter(img, g, 'replicate'); %图像滤波
gray_img=rgb2gray(g_img); %转为灰色图像
open = imopen(gray_img,se1); %图像开操作
sub_img = imsubtract(gray_img,open); %图像相减
BW_img = imbinarize(sub_img); %使用Otsu方法确定全局阈值进行二值化
edge_img = edge(BW_img,'canny');
edge_img1 = imclose(edge_img,se2); %图像闭操作
edge_img2 = imopen(edge_img1,se3); %图像开操作
%%%%%%%%%%%%%%%%%%%%%%%%%%%使用车牌长宽比进行判断%%%%%%%%%%%%%%%%%%%%%%%%%%%
[B,L] = bwboundaries(edge_img2,'noholes');
num_rect = 0; %符合要求的矩形数量
matrix_rect = {}; %符合要求的矩形的坐标元胞矩阵
for k = 1:length(B)
boundary = B{k};
c = boundary(:,2);
r = boundary(:,1);
[rectx,recty,area,perimeter] = minboundrect(c,r,'a'); %rectx,recty为逆时针排列
width = round(sqrt((recty(1)-recty(2))^2+(rectx(1)-rectx(2))^2));
leth = round(sqrt((recty(2)-recty(3))^2+(rectx(2)-rectx(3))^2));
if width > leth
temp = width;
width = leth;
leth = temp;
end
ratio = leth / width;
if ratio >2.5 && ratio <4.5
num_rect = num_rect + 1;
matrix_rect{num_rect} = [rectx,recty];
end
end
subplot(451); imshow(img); title('原始图像');
subplot(452); imshow(g_img); title('高通滤波后图像');
subplot(453); imshow(gray_img); title('灰度图像');
subplot(454); imshow(open); title('图像开操作');
subplot(455); imshow(sub_img); title('图像相减');
subplot(456); imshow(BW_img); title('图像二值化');
subplot(457); imshow(edge_img); title('图像边缘');
subplot(458); imshow(edge_img2); title('图像开闭操作');
subplot(459); imshow(img); title('原图框出车牌');
hold on
for k = 1:num_rect
rect = matrix_rect{k};
rx = rect(:,1);
ry = rect(:,2);
line(rx,ry,'Color','red');
end
%%%%%%%%%%%%%%%%%%%%%%%%%%%判断颜色、二次判断车牌%%%%%%%%%%%%%%%%%%%%%%%%%%%
p=0; %计算满足颜色条件的次数
color = 'no';
for o=1:num_rect
z=matrix_rect{o};
mid1x=(z(1,1)+z(2,1))/2;
mid1y=(z(1,2)+z(2,2))/2;
mid2x=(z(3,1)+z(4,1))/2;
mid2y=(z(3,2)+z(4,2))/2;
green=0;blue=0;
hsv= rgb2hsv(img); %RGB转换为HSV
img_count = (abs(ceil(mid2x+0.601)-floor(mid1x+0.601)))*(abs(ceil(mid2y+0.001)-floor(mid1y+0.001)));
subplot(4,5,10); imshow(hsv);
for i=ceil(mid1y+1):floor(mid2y-1)
if mid2x==mid1x
for j=floor(mid2x+1):ceil(mid1x+1)
h = hsv(i,j,1);
s = hsv(i,j,2);
v = hsv(i,j,3);
if 0.40< h && h <= 0.46 && s>0.4 && s<=1 && v>0.3 && v<1
green = green+1;
elseif 0.56<h && h<=0.72 && s>0.4 && s<=1 && v>0.4 && v<1
blue =blue +1;
end
end
else
for j=ceil(mid2x+1):floor(mid1x-1)
h = hsv(i,j,1);
s = hsv(i,j,2);
v = hsv(i,j,3);
if 0.40< h && h <= 0.46 && s>0.4 && s<=1 && v>0.3 && v<1
green = green+1;
elseif 0.56<h && h<=0.72 && s>0.4 && s<=1 && v>0.4 && v<1
blue =blue +1;
end
end
end
end
if green*2 >= img_count && green>blue
color = 'green';
p=p+1;
b=z; %满足条件的元胞
elseif blue*2 >= img_count && blue>green
color = 'blue';
p=p+1;
b=z; %满足条件的元胞
end
end
if (color == 'blue')&&(p == 1)
flag = 0;
style = '识别到的是蓝色';
elseif (color == 'green')&&(p == 1)
flag = 1;
style = '识别到的是新能源';
end
function image=cutting(img,flag)
%获取图片大小
[row,col] = size(img);
%设定边界
img(:,col)=1;
img(:,1)=1;
%图像取反，方便后续处理，根据黑色判断边界
all = sum(~img); %行向量
%figure('NumberTitle','off','Name','投影'),bar(a),title('投影');
left = 1;
right = 1;
count1 =0; %记录字符个数
for i = 1:col-1 %从左到右扫描
if all(i)==0&&all(i+1)~=0 %左侧边界
left = i;
end
if all(i)~=0&&all(i+1)==0 %右侧边界
right=i;
else
right =0; %左右两侧均为黑色边框
end
if right~=0
count1 = count1+1;
left_bound(count1) = left; %存放左边界
right_bound(count1) = right; %存放右边界
end
end
for i = 1:count1 %？？？
if left_bound(i)<fix(col/8)
left_bound(i)=left_bound(1);
end
end
count2 =1; %k记录满足条件的字符个数
right_boundary = zeros(1,count1); %存放右边界
left_boundary = zeros(1,count1); %存放左边界
for i = 1:count1
if (right_bound(i) - left_bound(i))>(fix(col/15)) %判断字符宽度是否满足要求 问题：字符宽度怎么求
right_boundary(count2) = right_bound(i);
left_boundary(count2) = left_bound(i);
count2 = count2+1;
end
end
三、运行结果
4 参考文献
[1]魏武, 张起森, 王明俊,等. 一种基于模板匹配的车牌识别方法[J]. 中国公路学报, 2001, 14(001):104-106.
### 博主简介：擅长智能优化算法、神经网络预测、信号处理、元胞自动机、图像处理、路径规划、无人机等多种领域的Matlab仿真，相关matlab代码问题可私信交流。
**部分理论引用网络文献，若有侵权联系博主删除。**
