Open CV Tutorial - Advanced operations on images ' Filter color in Image'

In this tutorial we will learn to filter images, and separate the color. For this I am using Opencv library. In my earlier posts I have discussed how to link opencv in devC++ (here) and in Visual Studio (here). Here I suppose that you know the basic of image processing and programing using opencv.

Here I have given a very basic algo to filter color which will not work with real life images, but will give a insight how to loop through each and every pixel of a image. In this code we will loop through each pixel, find the value of each component ( RGB) and for a specific condition we will determine that pixel is of which color. Here I have Used two functions

CvScalar cvGet2D( const CvArr* arr, int idx0, int idx1 )
->
void cvSet2D( CvArr* arr, int idx0, int idx1, CvScalar value );
-> Note that cvSet*D function can be used safely for both single-channel and multiple-channel arrays though they are a bit slower.

/******************** CODE TO FILTER COLORS ****************/
#include
#include
#include
#include

int main()
{
 // Decleare image variables
    IplImage* img=0; // original image
    IplImage* white;
    IplImage* blue;     
    IplImage* green;     
    IplImage* red;     
    
    
    //load original image
    img = cvLoadImage("test.jpg",-1);
    if(img==0)
    {
              printf(" ERORR IN LOADING IMAGE !!");
              exit(-1);
    }
    
    // get height and width for image
    int height=img->height;
 int width=img->width;
    
    // create four images
    white=cvCreateImage(cvSize(img->width,img->height),8,1);
    
    blue=cvCreateImage(cvSize(img->width,img->height),8,3);
    green=cvCreateImage(cvSize(img->width,img->height),8,3);
    red=cvCreateImage(cvSize(img->width,img->height),8,3);
    // Two scalar variable to store a pixle data.
    // wt -> white 
    CvScalar s,wt;
    wt.val[0]=255;
    
    // A very simple filter operation
    // This loops through each and every pixle of image and filter accordingly
    for(int i=0;i100 && s.val[1]>100 && s.val[2]>100) // filter white
                cvSet2D(white,i,j,wt);
      
        else if(s.val[0]>100 && s.val[1]<100 && s.val[2]<100) // filter blue
               cvSet2D(blue,i,j,s);
               
        else if(s.val[0]<100 && s.val[1]>100 && s.val[2]<100) // filter green
               cvSet2D(green,i,j,s);
        
        else if(s.val[0]<100 && s.val[1]<100 && s.val[2]>100) // filter red
               cvSet2D(red,i,j,s);
        
     
     }
     

    // Create windows and show them
 cvNamedWindow("img", 1);
 cvShowImage( "img", img );

    cvNamedWindow("white", 1);
 cvShowImage( "white", white );
 
    cvNamedWindow("blue", 1);
 cvShowImage( "blue",blue);
 
 cvNamedWindow("green", 1);
 cvShowImage( "green",green);
 
 cvNamedWindow("red", 1);
 cvShowImage( "red",red);

 // Wait for any to be pressed      
    cvWaitKey(0);

 // Detroy all created windows
 cvDestroyAllWindows();

 // Release the memory occupied by images
    cvReleaseImage( &img );
 cvReleaseImage( &white);
 cvReleaseImage( &blue);
 cvReleaseImage( &green);
 cvReleaseImage( &red);

 return 0;
}

OUTPUT:- 

 test.jpg :-                                       red image:-                       blue image :-                                            

        Green Image                                                                    White Image

ALSO READ :- 

• Open CV Tutorial and Introduction
• Linking OpenCV library in DEVC++
• OPENCV Tutorial - Basic operations for images Dilate/Erode

• Open CV Tutorial - Basic operations for images ' Canny edge detection'