Montag, 22. Juli 2013

FACE DETECTION - MATLAB CODE

                                  Lets see how to detect face, nose, mouth and eyes using the MATLAB built-in class and function. Based on Viola-Jones face detection algorithm, the computer vision system toolbox contains vision.CascadeObjectDetector System object which detects objects based on above mentioned algorithm.
  
Prerequisite: Computer vision system toolbox

FACE DETECTION:

clear all
clc
%Detect objects using Viola-Jones Algorithm

%To detect Face
FDetect = vision.CascadeObjectDetector;

%Read the input image
I = imread('HarryPotter.jpg');

%Returns Bounding Box values based on number of objects
BB = step(FDetect,I);

figure,
imshow(I); hold on
for i = 1:size(BB,1)
    rectangle('Position',BB(i,:),'LineWidth',5,'LineStyle','-','EdgeColor','r');
end
title('Face Detection');
hold off;



The step(Detector,I) returns Bounding Box value that contains [x,y,Height,Width] of the objects of interest.


BB =

    52    38    73    73
   379    84    71    71
   198    57    72    72

NOSE DETECTION:


%To detect Nose
NoseDetect = vision.CascadeObjectDetector('Nose','MergeThreshold',16);



BB=step(NoseDetect,I);


figure,
imshow(I); hold on
for i = 1:size(BB,1)
    rectangle('Position',BB(i,:),'LineWidth',4,'LineStyle','-','EdgeColor','b');
end
title('Nose Detection');
hold off;





EXPLANATION:


To denote the object of interest as 'nose', the argument  'Nose' is passed.

vision.CascadeObjectDetector('Nose','MergeThreshold',16);

The default syntax for Nose detection :
vision.CascadeObjectDetector('Nose');

Based on the input image, we can modify the default values of the parameters passed to vision.CascaseObjectDetector. Here the default value for 'MergeThreshold' is 4.

When default value for 'MergeThreshold' is used, the result is not correct.
Here there are more than one detection on Hermione.




To avoid multiple detection around an object, the 'MergeThreshold' value can be overridden. 


MOUTH DETECTION:



%To detect Mouth
MouthDetect = vision.CascadeObjectDetector('Mouth','MergeThreshold',16);

BB=step(MouthDetect,I);


figure,
imshow(I); hold on
for i = 1:size(BB,1)
 rectangle('Position',BB(i,:),'LineWidth',4,'LineStyle','-','EdgeColor','r');
end
title('Mouth Detection');
hold off;



EYE DETECTION:


%To detect Eyes
EyeDetect = vision.CascadeObjectDetector('EyePairBig');

%Read the input Image
I = imread('harry_potter.jpg');

BB=step(EyeDetect,I);



figure,imshow(I);
rectangle('Position',BB,'LineWidth',4,'LineStyle','-','EdgeColor','b');
title('Eyes Detection');
Eyes=imcrop(I,BB);
figure,imshow(Eyes);







Cropped Image


I will discuss more about object detection and how to train detectors to identify object of our interest in my upcoming posts. Keep reading for updates.

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