Face detector using Matlab

Face  detector  using Matlab 


first we have to write program of face detection  using Matlab and

face detection program :

% Create a cascade detector object.
faceDetector = vision.CascadeObjectDetector();

% Read a video frame and run the detector.
videoFileReader = vision.VideoFileReader('visionface.avi');
videoFrame      = step(videoFileReader);
bbox            = step(faceDetector, videoFrame);

% Draw the returned bounding box around the detected face.
videoOut = insertObjectAnnotation(videoFrame,'rectangle',bbox,'Face');
figure, imshow(videoOut), title('Detected face');

% Get the skin tone information by extracting the Hue from the video frame
% converted to the HSV color space.
[hueChannel,~,~] = rgb2hsv(videoFrame);

% Display the Hue Channel data and draw the bounding box around the face.
figure, imshow(hueChannel), title('Hue channel data');
rectangle('Position',bbox(1,:),'LineWidth',2,'EdgeColor',[1 1 0])

% Detect the nose within the face region. The nose provides a more accurate
% measure of the skin tone because it does not contain any background
% pixels.
noseDetector = vision.CascadeObjectDetector('Nose');
faceImage    = imcrop(videoFrame,bbox(1,:));
noseBBox     = step(noseDetector,faceImage);

% The nose bounding box is defined relative to the cropped face image.
% Adjust the nose bounding box so that it is relative to the original video
% frame.
noseBBox(1,1:2) = noseBBox(1,1:2) + bbox(1,1:2);

% Create a tracker object.
tracker = vision.HistogramBasedTracker;

% Initialize the tracker histogram using the Hue channel pixels from the
% nose.
initializeObject(tracker, hueChannel, noseBBox(1,:));

% Create a video player object for displaying video frames.
videoInfo    = info(videoFileReader);
videoPlayer  = vision.VideoPlayer('Position',[300 300 videoInfo.VideoSize+30]);

% Track the face over successive video frames until the video is finished.
while ~isDone(videoFileReader)

    % Extract the next video frame
    videoFrame = step(videoFileReader);

    % RGB -> HSV
    [hueChannel,~,~] = rgb2hsv(videoFrame);

    % Track using the Hue channel data
    bbox = step(tracker, hueChannel);

    % Insert a bounding box around the object being tracked
    videoOut = insertObjectAnnotation(videoFrame,'rectangle',bbox,'Face');

    % Display the annotated video frame using the video player object
    step(videoPlayer, videoOut);

end

% Release resources
release(videoFileReader);
release(videoPlayer);

 



the above program detects the face as a test face 
when we use this program it match the test image by the available image and if it match it display as the face name as we  given to the face and , the face name is display on the screen of matlab figure 

Matlab has many applications cheak thi out , its will be funy http://makerzone.mathworks.com/?s_eid=PSM_6556