Fastest Face Detection in Matlab with source code

Overview:
      In this article I am going to show you the simplest and fastest method to implement a face detection code in MATLAB 2012
                           

Things to know:

• Haar-like features 
• Voila-jones Method 
• MATLAB Basic image processing 

Test Image:

     In this article to test the code we are using the famous Lenna Image.

Detailed working and code demonstrations:
         In MATLAB 2012 there is a Computer Vision library which is used in this proposed code. Which implements the Voila-jones method to detect the haar-like features of frontal face.
Here's what Wikipedia says about Haar-like features 

Haar-like features are digital image features used in object recognition. They owe their name to their intuitive similarity with Haar wavelets and were used in the first real-time face detector.

and  about voila-jones method

The Viola–Jones object detection framework is the first object detection framework to provide competitive object detection rates in real-time proposed in 2001 by Paul Viola and Michael Jones.

Coding:

    First of all read the lenna image from your disk using imread command

 x = imread('lenna.jpg');  

Then Create a Detector object using Vission Library of MATLAB

 det_face =  vision.CascadeObjectDetector('FrontalFaceCART');  

Now get the bounding box of face from RGB image of lenna readed in variable x 
This will be done using step function 

 bbox_face = step(det_face,x);    
 [M N]=size(bbox_face);  
 if(M>0)  
   %if any face is detected   
     bbox_face = bbox_face(1,:); %assumed there is only one face in image  
     face_croped = imcrop(x,int32(bbox_face)); %crop the face   
     figure,imshow(face_croped);  
      title('face');  
      %to draw the rectangle   
      figure,imshow(x);hold on   
     rectangle('Position',int32(bbox_face), 'LineWidth',2, 'EdgeColor','g');  
     hold off  
 else   
   msgbox('No face is detected');    
 end  
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