Face mask in opencv

Input: face image

Problem: thresholded image before applying Canny to find contours but does not return face mask

Desired output if different face is input,it should generate a proper face mask(face area white and background white)

Tried with apple picture..works fine

            #include <opencv2/highgui/highgui.hpp>
            #include <opencv2/core/core.hpp>
            #include <opencv2/imgproc/imgproc.hpp>

            using namespace cv;
            using namespace std;

            int main(){
              Mat right=imread("front.jpg");
              Mat img1;
              cvtColor(right, img1, CV_RGB2GRAY);
              threshold(img1,img1,160,255,cv::THRESH_BINARY);
              Canny(img1, img1, 128, 350);
              vector< vector<Point> > contours;
              findContours(img1, contours, CV_RETR_EXTERNAL, CV_CHAIN_APPROX_NONE);
              Mat mask = Mat::zeros(img1.rows, img1.cols, CV_8UC1);
              drawContours(mask, contours, -1, Scalar(255), CV_FILLED);
              normalize(mask.clone(), mask, 0.0, 255.0, CV_MINMAX, CV_8UC1);

              imshow("original", right);
              imshow("thresh",img1);
              imshow("mask", mask);

              waitKey(0);
              return 0;
    }

Here is the image that I used

Please ignore the first 3 comments below

Using this below code the mask creation working perfectly for the sample image you provided in the above commants.

Here assumes, your background is of any colour with no other object.

The below code will do

Find edge
Strengthen the edge by morphology operation.
Find biggest contour in edge( always the boundary of your foreground ) and draw it by filling.

Sometimes your contour may not be closed at the bottom(no edges at bottom) so the filling contour wont work, so for make it closed the code first find the bounding rect for biggest contour(foreground) and then draw bottom of rect to the edge image, then find largest contour again will give you the proper mask image.

Rect R;

Mat findLargestContour(Mat thr){

vector< vector <Point> > contours; // Vector for storing contour
vector< Vec4i > hierarchy;
int largest_contour_index=0;
int largest_area=0;
Mat dst(thr.rows,thr.cols,CV_8UC1,Scalar::all(0)); //create destination image

findContours( thr, contours, hierarchy,CV_RETR_EXTERNAL, CV_CHAIN_APPROX_SIMPLE );
for( int i = 0; i< contours.size(); i++ ) // iterate through each contour.
      {
       double a=contourArea( contours[i],false);  //  Find the area of contour
       if(a>largest_area){
       largest_area=a;
       largest_contour_index=i;                //Store the index of largest contour
       }
      }
drawContours( dst,contours, largest_contour_index, Scalar(255,255,255),CV_FILLED, 8, hierarchy );
R= boundingRect( contours[largest_contour_index]);
return dst;

}

int main( )
{

              Mat right=imread("1.jpg");
           // blur(right,right,Size(3,3));
              Mat gray;
              cvtColor(right, gray, CV_RGB2GRAY);

              int borderW=10;
              //Mat ROI=gray(Rect(borderW,borderW,img1.cols-2*borderW,img1.rows-2*borderW));
              Canny(gray, gray, 30, 255);

              Size kernalSize (5,5);
              Mat element = getStructuringElement (MORPH_RECT, kernalSize, Point(1,1)  );
              morphologyEx(gray, gray, MORPH_CLOSE, element );
              imshow("canny", gray);

              Mat largestCon=findLargestContour(gray.clone());
              line(largestCon, Point(R.x,R.y+R.height), Point(R.x+R.width,R.y+R.height), Scalar(255),2,8,0);

              Mat mask=findLargestContour(largestCon.clone());

              Mat A;
              right.copyTo(A,mask);
              imshow("original", right);
              imshow("dst", A);
              imshow("mask", mask);

              waitKey(0);


  return 0;
  }

See some sample mask