Detecting blobs using cvblobs library

A blob in image processing is often defined as a group of connected pixels with same logical state. Blob analysis is often used to detect a moving object in  real time image processing.

cvblobs is a blob library for OpenCV available at http://code.google.com/p/cvblob/

To use this library in codeblocks just unzip the downloaded library and copy the cvblob.h header file to the headers directory in opencv in my case it is C:\opencv2.0\include\opencv.

Then add the rest of the files to your project by right clicking on the project and selecting add files.

Here is a example for tracking an yellow  colored object using this blob library

//OpenCV Headers
#include<cv.h>
#include<highgui.h>
//Input-Output
#include<stdio.h>
//Blob Library Headers
#include<cvblob.h>
//Definitions
#define h 240
#define w 320
//NameSpaces
using namespace cvb;
using namespace std;
int main()
{
//Structure to get feed from CAM
CvCapture* capture=cvCreateCameraCapture(0);
//Structure to hold blobs
CvBlobs blobs;
//Windows
cvNamedWindow("Live",CV_WINDOW_AUTOSIZE);
//Image Variables
IplImage *frame=cvCreateImage(cvSize(w,h),8,3);   //Original Image
IplImage *hsvframe=cvCreateImage(cvSize(w,h),8,3);//Image in HSV color space
IplImage *labelImg=cvCreateImage(cvSize(w,h),IPL_DEPTH_LABEL,1);//Image Variable for blobs
IplImage *threshy=cvCreateImage(cvSize(w,h),8,1); //Threshold image of yellow color

//Getting the screen information
int screenx = GetSystemMetrics(SM_CXSCREEN);
int screeny = GetSystemMetrics(SM_CYSCREEN);

while(1)
{
//Getting the current frame
IplImage *fram=cvQueryFrame(capture);
//If failed to get break the loop
if(!fram)
break;
//Resizing the capture
cvResize(fram,frame,CV_INTER_LINEAR );
//Flipping the frame
cvFlip(frame,frame,1);
//Changing the color space
cvCvtColor(frame,hsvframe,CV_BGR2HSV);
//Thresholding the frame for yellow
cvInRangeS(hsvframe,cvScalar(23,41,133),cvScalar(40,150,255),threshy);
//Filtering the frame
cvSmooth(threshy,threshy,CV_MEDIAN,7,7);
//Finding the blobs
unsigned int result=cvLabel(threshy,labelImg,blobs);
//Rendering the blobs
cvRenderBlobs(labelImg,blobs,frame,frame);
//Filtering the blobs
cvFilterByArea(blobs,60,500);
for (CvBlobs::const_iterator it=blobs.begin(); it!=blobs.end(); ++it)
{
double moment10 = it->second->m10;
double moment01 = it->second->m01;
double area = it->second->area;
//Variable for holding position
int x1;
int y1;
//Calculating the current position
x1 = moment10/area;
y1 = moment01/area;
//Mapping to the screen coordinates
int x=(int)(x1*screenx/w);
int y=(int)(y1*screeny/h);
//Printing the position information
cout<<"X: "<<x<<" Y: "<<y<<endl;
}
//Showing the images
cvShowImage("Live",frame);
//Escape Sequence
char c=cvWaitKey(33);
if(c==27)
break;
}
//Cleanup
cvReleaseCapture(&capture);
cvDestroyAllWindows();

}

Here we are taking live feed from the cam and thresholding it for yellow color. Then we are smoothing it with a median filter and finding the blobs. Then we are rendering them so that we can see them. cvFilterByArea removes any blobs which are too big or too small to be called a blob. Then we are finding their moments,dividing them by their area we get the X and Y positions.

The result is as follows