基于MATLAB模板匹配的车牌识别系统设计与实现（附字符模板库）

grayImg = rgb2gray(imread('car_plate.jpg'));

bwImg = imbinarize(grayImg, 'adaptive', 'Sensitivity', 0.5);

se = strel('rectangle', [3,3]); processedImg = imclose(bwImg, se);  % 闭运算填充空洞

edges = edge(processedImg, 'Sobel');

stats = regionprops(edges, 'BoundingBox', 'Area'); 
plateRegion = stats(find([stats.Area] > 5000, 1));  % 面积阈值过滤

verticalProj = sum(processedImg, 1);
[peaks, locs] = findpeaks(verticalProj, 'MinPeakDistance', 10);
charRegions = imcrop(processedImg, [locs(1), 1, locs(end)-locs(1)+1, size(processedImg,1)]);

templates = loadTemplates();  % 加载模板函数（见下文）

charImg = imresize(imcrop(charRegions, [x,y,w,h]), [32,32]);
scores = zeros(size(templates));
for i = 1:numel(templates)
    scores(i) = normxcorr2(templates(i).img, charImg);
end
[~, idx] = max(scores);
recognizedChar = templates(idx).name;

function templates = loadTemplates()
    templates = struct();
    % 数字模板
    for i = 0:9
        img = imread(sprintf('templates/%d.png', i));
        templates(sprintf('%d',i)).img = imresize(img, [32,32]);
        templates(sprintf('%d',i)).name = sprintf('%d',i);
    end
    % 字母模板
    chars = 'ABCDEFGHIJKLMNOPQRSTUVWXYZ';
    for i = 1:numel(chars)
        img = imread(sprintf('templates/%s.png', chars(i)));
        templates(chars(i)).img = imresize(img, [32,32]);
        templates(chars(i)).name = chars(i);
    end
    % 汉字模板（示例）
    chineseChars = {'京','沪','粤'};
    for i = 1:numel(chineseChars)
        img = imread(sprintf('templates/%s.png', chineseChars{i}));
        templates(chineseChars{i}).img = imresize(img, [32,32]);
        templates(chineseChars{i}).name = chineseChars{i};
    end
end

%% 车牌识别主程序
img = imread('car_plate.jpg');
grayImg = rgb2gray(img);
bwImg = imbinarize(grayImg, 'adaptive');
​
% 形态学处理
se = strel('rectangle', [3,3]);
processedImg = imclose(bwImg, se);
​
% 车牌定位
edges = edge(processedImg, 'Sobel');
stats = regionprops(edges, 'BoundingBox', 'Area');
plateRegion = stats(find([stats.Area] > 5000, 1)).BoundingBox;
​
% 字符分割
plateImg = imcrop(processedImg, plateRegion);
verticalProj = sum(plateImg, 1);
[peaks, locs] = findpeaks(verticalProj, 'MinPeakDistance', 10);
charRegions = cell(1,numel(locs)-1);
for i = 1:numel(locs)-1
    charRegions{i} = imcrop(plateImg, [locs(i),1,locs(i+1)-locs(i),size(plateImg,1)]);
end
​
% 字符识别
templates = loadTemplates();
plateNumber = '';
for i = 1:numel(charRegions)
    charImg = imresize(charRegions{i}, [32,32]);
    scores = zeros(size(templates));
    for j = 1:numel(templates)
        scores(j) = normxcorr2(templates(j).img, charImg);
    end
    [~, idx] = max(scores);
    plateNumber = [plateNumber, templates(idx).name];
end
disp(['识别结果：', plateNumber]);