疲劳驾驶检测matlab图像处理Code.zip

clc; clear all; close all; %% load DB load svm cl = {'open','close'}; dim = [30 60; 30 60 40 65]; delete(imaqfind) vid=videoinput('winvideo',1); triggerconfig(vid,'manual'); set(vid,'FramesPerTrigger',1 ); set(vid,'TriggerRepeat', Inf); % start(vid); % View the default color space used for the data � The value of the ReturnedColorSpace property indicates the color space of the image data. color_spec=vid.ReturnedColorSpace; % Modify the color space used for the data � To change the color space of the returned image data, set the value of the ReturnedColorSpace property. if ~strcmp(color_spec,'rgb') set(vid,'ReturnedColorSpace','rgb'); end start(vid) % Create a detector object faceDetector = vision.CascadeObjectDetector; faceDetectorLeye = vision.CascadeObjectDetector('EyePairBig'); faceDetectorM = vision.CascadeObjectDetector('Mouth'); tic % Initialise vector LC = 0; % Left eye closer RC = 0; % Right eye closer MC = 0; % Mouth closer TF = 0; % Total frames TC = 0; % Total closure Feature = []; c1p = 1; species = 'Non-Fatigue'; for ii = 1:600 trigger(vid); im=getdata(vid,1); % Get the frame in im imshow(im) subplot(3,4,[1 2 5 6 9 10]); imshow(im) % Detect faces bbox = step(faceDetector, im); if ~isempty(bbox); bbox = bbox(1,:); % Plot box rectangle('Position',bbox,'edgecolor','r'); S = skin_seg2(im); % Segment skin region bw3 = cat(3,S,S,S); % Multiply with original image and show the output Iss = double(im).*bw3; Ic = imcrop(im,bbox); Ic1 = imcrop(Iss,bbox); subplot(3,4,[3 4]); imshow(uint8(Ic1)) bboxeye = step(faceDetectorLeye, Ic); if ~isempty(bboxeye); bboxeye = bboxeye(1,:); Eeye = imcrop(Ic,bboxeye); % Plot box rectangle('Position',bboxeye,'edgecolor','y'); else disp('Eyes not detected') end if isempty(bboxeye) continue; end Ic(1:bboxeye(2)+2*bboxeye(4),:,:) = 0; % Detect Mouth bboxM = step(faceDetectorM, Ic); if ~isempty(bboxM); bboxMtemp = bboxM; if ~isempty(bboxMtemp) bboxM = bboxMtemp(1,:); Emouth = imcrop(Ic,bboxM); % Plot box rectangle('Position',bboxM,'edgecolor','y'); else disp('Mouth not detected') continue; end else disp('Mouth not detected') continue; end [nre nce k ] = size(Eeye); % Divide into two parts Leye = Eeye(:,1:round(nce/2),:); Reye = Eeye(:,round(nce/2+1):end,:); subplot(3,4,7) imshow(edge(rgb2gray(Leye),'sobel')); subplot(3,4,8) imshow(edge(rgb2gray(Reye),'sobel')); Emouth3 = Emouth; Leye = rgb2gray(Leye); Reye = rgb2gray(Reye); Emouth = rgb2gray(Emouth); % K means clustering X = Emouth(:); [nr1 nc1 ] = size(Emouth); cid = kmeans(double(X),2,'emptyaction','drop'); kout = reshape(cid,nr1,nc1); subplot(3,4,[11,12]); % Segment Ism = zeros(nr1,nc1,3); % Ism(:,:,3) = 255; % Ism(:,:,3) = 125; Ism(:,:,3) = 255; bwm = kout-1; bwm3 = cat(3,bwm,bwm,bwm); Ism(logical(bwm3)) = Emouth3(logical(bwm3)); imshow(uint8(Ism)); % Template matching using correlation coefficient % Left eye % Resize to standard size Leye = imresize(Leye,[dim(1,1) dim(1,2)]); c1 =match_DB(Leye,DBL); subplot(3,4,7) title(cl{c1}) % Right eye % Resize to standard size Reye = imresize(Reye,[dim(2,1) dim(2,2)]); c2 = match_DB(Reye,DBR); subplot(3,4,8) title(cl{c2}) % Mouth % Resize to standard size Emouth = imresize(Emouth,[dim(3,1) dim(3,2)]); c3 = match_DB(Emouth,DBM); subplot(3,4,[11,12]); title(cl{c3}) if c1 == 2 LC = LC+1; if c1p == 1 TC = TC+1; end end if c2==2 RC = RC+1; end if c3 == 1 MC = MC + 1; end TF = TF + 1; % Total frames toc if toc>8 Feature = [LC/TF RC/TF MC/TF TC] species = svmclassify(svmStruct,Feature); tic % Initialise vector LC = 0; % Left eye closer RC = 0; % Right eye closer MC = 0; % Mouth closer TF = 0; % Total frames TC = 0; % Total closure end subplot(3,4,[1 2 5 6 9 10]); if strcmpi(species,'Fatigue') text(20,20,species,'fontsize',14,'color','r','Fontweight','bold') beep; else text(20,20,species,'fontsize',14,'color','g','Fontweight','bold') end c1p = c1; pause(0.00005) end end