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c++ - Masking a blob from a binary image

I am doing motion recognition of walking using openCV and C++ and I would like to create a mask or copied image in order to achieve the effect seen in the picture provided. extracted human.The following is an explanation of the images The resulting blob of the human walking is seen. Then, a mask image or copied image of the original frame is created, the binary human blob is now masked and the non-masked pixels are now set to zero. The result is the extracted human body with a black background. The diagram below shows how the human blob is extracted and then masked. This is to be done for every 5th frame of a video sequence. My code so far consists of getting every 5th frame, grayscaling it, finding the areas of all the blobs, and applying a threshold value to get a binary image where more or less, only the human blob is white and the rest of the image is black. Now, I am trying to extract the human body but I have no clue how to proceed. Please help me.

#include "cv.h"
#include "highgui.h"
#include "iostream"

using namespace std;
int main( int argc, char* argv ) {

CvCapture *capture = NULL;
capture = cvCaptureFromAVI("C:\walking\lady walking.avi");
if(!capture){
    return -1;
}

IplImage* color_frame = NULL;
IplImage* gray_frame = NULL ;

int thresh_frame = 28;
CvMoments moments;

int frameCount=0;//Counts every 5 frames
cvNamedWindow( "walking", CV_WINDOW_AUTOSIZE );

while(1) {
    color_frame = cvQueryFrame( capture );//Grabs the frame from a file
    if( !color_frame ) break;
    gray_frame = cvCreateImage(cvSize(color_frame->width, color_frame->height), color_frame->depth, 1);
    if( !color_frame ) break;// If the frame does not exist, quit the loop


    frameCount++;
    if(frameCount==5)
    {
        cvCvtColor(color_frame, gray_frame, CV_BGR2GRAY);
        cvThreshold(gray_frame, gray_frame, thresh_frame, 255, CV_THRESH_BINARY);
        cvErode(gray_frame, gray_frame, NULL, 1);
        cvDilate(gray_frame, gray_frame, NULL, 1);

        cvMoments(gray_frame, &moments, 1);
        double m00;
        m00 = cvGetCentralMoment(&moments, 0,0);

        cvShowImage("walking", gray_frame);
        frameCount=0;
    }
    char c = cvWaitKey(33);
    if( c == 27 ) break;
}

double m00 = (double)cvGetCentralMoment(&moments, 0,0);
cout << "Area - : " << m00 << endl;
//area of lady walking = 39696. Therefore, using new threshold area as 30 for this video
//area of walking man = 67929

cvReleaseImage(&color_frame);
cvReleaseImage(&gray_frame);
cvReleaseCapture( &capture );
cvDestroyWindow( "walking" );

return 0;
}

I would also like to upload the video that I am using in the code but I don't know how to upload it here, so if anyone can help me out with that too. I want to provide as much info as possible w.r.t. my question.

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1 Answer

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the easiest way is to look for the biggest blob in the image (cvfind contours can be the function you need), then you set to blac all the other blobs (scannig all the contours and using cvfloadfill). finally you scan the entire binary image if the considered pixel is white you do nothing, if the pixel is black you set to black the corresponding pixel of the 5th frame


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