车道检测.zip

%% 初始化 % 使用这些来初始化下部分代码的一些变量和系统对象 DrawPoly = 1; % 设置为0以绘制直线 NumRows = 120; % 要处理的视频区的行数（视图下部） MaxLaneNum = 20; % 跟踪库中保存的最大车道数目 ExpLaneNum = 2; % 当前视频帧中需要检测的最大车道数目 Rep_ref = zeros(2, MaxLaneNum); % 存储的车道线 Count_ref = zeros(1, MaxLaneNum); % 车道线计数 TrackThreshold = 75; % 在2帧视频之间车道区域允许的最大变动距离 LaneColors = single([0 0 0;1 1 0; 1 1 0; 1 1 1;1 1 1]); % 可以判定当前车道所需的最少帧数，即：5帧视频内未检测到偏离当前车道，则显示车道提示文本 frameFound = 5; % 车道标记有效的最多帧数，即：车道提示文本最多保持20个帧的时长 frameLost = 20; % 选择与原点距离为：35:45 (从1开始编号: 415:424)之间的直线 startIdxRho_R = 415; NumRhos_R = 11; % 选择斜率为：-90:-70deg (从1开始编号:: 1:21)之间的直线 startIdxTheta_R = 1; NumThetas_R = 21; % 选择与原点距离为：379:415 (从1开始编号:: 1:36)之间的直线 startIdxRho_L = 380; NumRhos_L = 36; % 对于斜率为：55:85deg (从1开始编号:: 146:176)的直线 startIdxTheta_L = 146; NumThetas_L = 21; % 显示车道线的偏移值 offset = int32([0, NumRows, 0, NumRows]); %% % 创建一个 |VideoFileReader| 系统对象以从文件读取视频 hVideoSrc = vision.VideoFileReader('viplanedeparture.avi'); %% % 创建一个 |HoughLines| 系统对象以检测黄白线的笛卡尔坐标 hHoughLines1 = vision.HoughLines('SineComputation', 'Trigonometric function'); % Hough变化介绍：https://www.cnblogs.com/lancer2015/p/6852488.html hHoughLines3 = vision.HoughLines('SineComputation', 'Trigonometric function'); %% % 定义插入的车道偏离时的警告文本参数。 warnText = {sprintf('Right\n Departure'), '', sprintf(' Left\n Departure')}; warnTextLoc = [120 170;-1 -1; 2 170]; %% % 定义插入的指定车道标记颜色/类型的文本参数 lineText = {'', ... sprintf('Yellow\nBroken'), sprintf('Yellow\nSolid'), ... sprintf('White\nBroken'), sprintf('White\nSolid')}; %% %创建一个 |VideoPlayer| 系统对象以输出显示视频 myVideoOut = vision.VideoPlayer; %% % 初始化在视频流循环处理中使用到的变量 Frame = 0; NumNormalDriving = 0; OutMsg = int8(-1); OutMsgPre = OutMsg; Broken = false; %% 视频流循环处理 % 创建一个循环过程来对给定视频进行车道线检测 % 该循环使用之前初始化的系统对象 warningTextColors = {[1 0 0], [1 0 0], [0 0 0], [0 0 0]}; while ~isDone(hVideoSrc) RGB = step(hVideoSrc); % 选择输入视频的下部（限制视野） Imlow = RGB(NumRows+1:end, :, :); % 边缘检测和Hough变换 Imlow = rgb2gray(Imlow); % Convert RGB to intensity I = imfilter(Imlow, [-1 0 1], 'replicate','corr'); %imfilter函数：对任意类型数组或多维图像进行滤波 % 设置饱和值为0到1之间 I(I < 0) = 0; I(I > 1) = 1; th = multithresh(I); % 计算门槛 [H, Theta, Rho] = hough(I > th); % 将角度制变量Theta转换成弧度制 Theta = Theta * pi / 180; % 峰值检测 H1 = H; % 删除H中满足下列条件的矩阵： theta < -78 deg and theta >= 78 deg H1(:, 1:12) = 0; H1(:, end-12:end) = 0; Idx1 = houghpeaks(H1, ExpLaneNum, 'NHoodSize', [301 81], 'Threshold', 1); Count1 = size(Idx1,1); % 根据峰值来选择Rhos和Thetas Line = [Rho(Idx1(:, 1)); Theta(Idx1(:, 2))]; Enable = [ones(1,Count1) zeros(1, ExpLaneNum-Count1)]; % 跟踪一组标记了的车道线 [Rep_ref, Count_ref] = videolanematching(Rep_ref, Count_ref, ... MaxLaneNum, ExpLaneNum, Enable, Line, ... TrackThreshold, frameFound+frameLost); % 将极值点转换到笛卡尔坐标系 Pts = step(hHoughLines1, Rep_ref(2,:), Rep_ref(1,:), Imlow); % 检测是否有向左或向右的车道偏离 [TwoValidLanes, NumNormalDriving, TwoLanes, OutMsg] = ... videodeparturewarning(Pts, Imlow, MaxLaneNum, Count_ref, ... NumNormalDriving, OutMsg); % 输出信息的含义: % 0 = 向右离开当前车道 % 1 = 正常驾驶 % 2 = 向左离开当前车道 % 检测车道线的颜色和类别 YCbCr = rgb2ycbcr(double(RGB(NumRows+1:240, :, :))); ColorAndTypeIdx = videodetectcolorandtype(TwoLanes, YCbCr); % 变量ColorAndTypeIdx的含义: % 无效的颜色或类别 = int8(0); % 黄虚线 = int8(1); % 黄实线 = int8(2); % 白虚线 = int8(3); % 白实线 = int8(4). % 输出 Frame = Frame + 1; if Frame >= 5 TwoLanes1 = TwoLanes + [offset; offset]'; if DrawPoly && TwoValidLanes if TwoLanes(4,1) >= 239 Templ = TwoLanes1(3:4, 1); else Templ = [0 239]'; end if TwoLanes(4,2) >= 239 Tempr = TwoLanes1(3:4, 2); else Tempr = [359 239]'; end Pts_poly = [TwoLanes1(:,1); Templ; Tempr; ... TwoLanes1(3:4,2); TwoLanes1(1:2,2)]; % 在车道区域绘制多边形 RGB = insertShape(RGB,'FilledPolygon',Pts_poly.',... 'Color',[0 1 1],'Opacity',0.2); end % 绘制车道线 RGB = insertShape(RGB,'Line',TwoLanes1',... 'Color',{'yellow','magenta'}); % 插入车道变更警告文本 (空文本不会被绘制) txt = warnText{OutMsg+1}; txtLoc = warnTextLoc(OutMsg+1, :); txtColor = single(warningTextColors{mod(Frame-1,4)+1}); RGB = insertText(RGB,txtLoc,txt,'TextColor', txtColor, ... 'FontSize',20, 'BoxOpacity', 0); % 插入描述车道线的颜色和种类信息的文本 for ii=1:2 % 空文本不会被绘制 txtLoc = TwoLanes1([1 2], ii)' + int32([0 -35]); lineTxt = lineText{ColorAndTypeIdx(ii)}; txtColor = LaneColors(ColorAndTypeIdx(ii), :); RGB = insertText(RGB,txtLoc,lineTxt,'TextColor',txtColor, ... 'FontSize',14, 'BoxOpacity', 0); end % 如果有必要，绘制第三条车道线 if OutMsgPre ~= OutMsg ColorType = ColorAndTypeIdx(2-(OutMsg == 2)); Broken = ColorType == 2 || ColorType == 4; end ShowThirdLane = Broken && (OutMsg~=1); if ShowThirdLane if OutMsg == 0 % 寻找位于右边的第三条车道线 Idx2 = houghpeaks(H(startIdxRho_R:startIdxRho_R+NumRhos_R-1, ... startIdxTheta_R:startIdxTheta_R+NumThetas_R-1), ... 'NHoodSize', [7 7], 'Threshold', 1); Rhor = Rho(Idx2(:,1) + startIdxRho_R); Thetar = Theta(Idx2(:,2) + startIdxTheta_R); ThirdLane = step(hHoughLines3, Thetar, Rhor, Imlow); else % 寻找位于左边的第三条车道线 Idx3 = houghpeaks(H(startIdxRho_L:startIdxRho_L+NumRhos_L-1 , ... startIdxTheta_L:startIdxTheta_L+NumThetas_L-1),... 'NHoodSize', [7 7], 'Threshold', 1); Rhol = Rho(Idx3(:,1) + startIdxRho_L); Thetal = Theta(Idx3(:,2) + startIdxTheta_L); ThirdLane = step(hHoughLines3, Thetal, Rhol, Imlow); end OutThirdLane = videoexclude3rdlane(ThirdLane, ShowThirdLane,... TwoLanes, TwoValidLanes, YCbCr); OutThirdLane = OutThirdLane(:) + offset(:); RGB = insertShape(RGB,'Line',OutThirdLane.','Color','green'); end end OutMsgPre = OutMsg; step(myVideoOut, RGB); % 显示视频 end %% 释放资源 release(hVideoSrc); %% 总结 % 在样例视频中，你可以看到【车道】、【车道线】以及【离开当前车道的方式】被检测到的过程 %% 附录 % 在这个例子中使用到的函数： % * <matlab:edit('videolanematching.m') videolanematching.m> % * <matlab:edit('videodeparturewarning.m') videodeparturewarning.m> % * <matlab:edit('videodetectcolorandtype.m') videodetectcolorandtype.m> % * <matlab:edit('videoexclude3rdlane.m