car.zip_matlab 车流量_手动画框检测_流量检测matlab_车流量_车流量检测matlab代码

clear all; close all; vehicle_num = 0; tempones = 0; block_info = zeros(4,4); % 用于存储虚拟检测框信息（[列，行，宽，高]） point_X = zeros(4,5); % 存储检测框点横坐标信息 point_Y = zeros(4,5); % 存储检测框点纵坐标信息 block_area = zeros(1,4); % 读入视频 videoObj = VideoReader('D:\matlabCode\cars\test 1.avi'); numFrames =videoObj.NumberOfFrames; FPS = videoObj.FrameRate; %获取帧率(fps) % 读入视频序列的第一帧作为初始值 newframe = read(videoObj, 1); fmed = double(newframe); [height, width, numColor]=size(newframe); figure(1); imshow(newframe); for i=1:4 k = waitforbuttonpress; % 等待鼠标按下 point1 = get(gca,'CurrentPoint'); % 鼠标按下了 finalRect = rbbox; % point2 = get(gca,'CurrentPoint'); % 鼠标松开了 point1 = point1(1,1:2); % 提取出两个点 point2 = point2(1,1:2); p1 = min(floor(point1),floor(point2)); % 计算位置 p2 = max(floor(point1),floor(point2)); offset = abs(floor(point1)-floor(point2)); % offset(1)表示宽，offset(2)表示高 x = [p1(1) p1(1)+offset(1) p1(1)+offset(1) p1(1) p1(1)]; y = [p1(2) p1(2) p1(2)+offset(2) p1(2)+offset(2) p1(2)]; hold on %防止plot时闪烁 plot(x,y,'r'); block_info(i,1:2) = round(point1(1,1:2)); block_info(i,3:4) = offset(1,1:2); block_area(i) = offset(1) * offset(2); point_X(i,1:5) = x(1,1:5); point_Y(i,1:5) = y(1,1:5); end % 近似中值背景模型参数阈值 Threh = 20; beta = 1.0; fg = zeros(height, width); %设置检测带参数 blockthresh = 0.5; % 阈值（面积大于该阈值则表示有车）！！！！！！最重要的参数 pre_stream_data = zeros(1,4); % 为了避免消耗过多的内存，每次只读取一个帧 for n = 1:numFrames %%%%！！！！！！numFrames可以调整 newframe = read(videoObj, n); %近似中值背景模型 Idiff = double(newframe) - fmed; pixInc = find(Idiff > 0); fmed(pixInc) = fmed(pixInc) + beta; pixDec = find(Idiff < 0); fmed(pixDec) = fmed(pixDec) - beta; fg = abs(Idiff) >Threh; if ( numColor == 3) fg = fg(:, :, 1) | fg(:, :, 2) | fg(:, :, 3); end % 图像显示 figure(1); % 原图 subplot(2,2,1), imshow(newframe); title(strcat('当前帧为No. ', int2str(n))); % 近似中值滤波分割结果 subplot(2,2,2), imshow(fg); title('近似中值滤波分割结果'); %%%%！！！！！！加入去阴影的代码 % 形态学滤波，消除噪点、填充车辆分割区域 % se=strel('square',3'); % 方型结构元素 % 可调整！！！！！！ se=strel('disk',3'); % 圆盘型结构元素 fg =imopen(fg,se); fg =imdilate(fg,se); subplot(2,2,3), imshow(fg); %%%%！！！！！！加入去阴影的代码 title('形态学滤波结果'); % 加入检测框 subplot(2,2,4), imshow(newframe); hold on; for i = 1:4 x = point_X(i,1:5); y = point_Y(i,1:5); plot(x,y,'r'); end % 对检测框提取数据信息，用来判断检测框内是否有车辆 cur_stream_data = zeros(1,4); for driveway = 1:4 % 总共4个车道 %%%%！！！！！！可随车道数目更改 % fg(起始行：终止行，起始列：终止列) start_row = block_info(driveway,2); % 起始行 end_row = block_info(driveway,2) + block_info(driveway,4) - 1; %终止行 start_column = block_info(driveway,1); % 起始列 end_column = block_info(driveway,1) + block_info(driveway,3) - 1; %终止列 fgstrip = fg(start_row:end_row,start_column:end_column); % 计算每个检测框中图像块中“1”的个数 block_sum = sum(sum(fgstrip)); % 该检测框像素总数（即面积） %block_area = block_info(driveway,3)*block_info(driveway,4); % 确定是否有车，如果该块中1的个数占该块像素总数的比例>= blockthresh. if block_sum/block_area(driveway) >= blockthresh % 表明检测框内有车，将cur_stream_data对应元素值置1 cur_stream_data(driveway) = 1; end end % 检测带状态变化及其设置 % 检测带状态变化 stream_change = cur_stream_data - pre_stream_data; %保存检测带车流状态，以便下一帧使用 pre_stream_data = cur_stream_data; % 将检测带车流状态变化量stream_change中的1置为0，（1对应车进入） stream_change(stream_change == 1) = 0; % 将检测带车流状态变化向量stream_change中的-1置为1，以便统计和显示 % 统计stream_change中连续1（即原-1）的个数超过stream_changewidth_thresh的段数，每段即表明通过一辆车 stream_change(stream_change == -1) = 1; % 统计车辆数 tempones = 0; for i = 1: size(stream_change, 2) if stream_change(i) vehicle_num = vehicle_num + 1; end end title(strcat('加入检测框，当前车辆数为', int2str(vehicle_num))); end