Filling elements 2 (the triangle problem)

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Actually, you can use the approxPolyDP() function and approximate your contours with accuracy proportional to the contour perimeter. Here is some code:

#include <iostream>
#include <opencv2/opencv.hpp>

using namespace std;
using namespace cv;
int main()
{
    /// Load image
    Mat src = imread( "holes.jpg");
    if( !src.data )
      { return -1; }

    // Show source image
    imshow("src", src);

    // Create binary image from source image
    Mat bw;
    cvtColor(src, bw, CV_BGR2GRAY);
    threshold(bw, bw, 40, 255, CV_THRESH_BINARY | CV_THRESH_OTSU);
    imshow("bin", bw);

    // Find contours
    vector<Vec4i> hierarchy;
    std::vector<std::vector<cv::Point> > contours;
    cv::findContours(bw.clone(), contours, hierarchy, CV_RETR_TREE, CV_CHAIN_APPROX_SIMPLE, Point(0, 0));

    // The array for storing the approximation curve
    std::vector<cv::Point> approx;

    // We'll put the labels in this destination image
    cv::Mat dst = Mat::zeros(bw.size(), CV_8UC1);

    // Loop through detected contours, and process accordingly
    for (int i = 0; i < contours.size(); i++)
    {
        // Approximate contour with accuracy proportional
        // to the contour perimeter with approxPolyDP. In this,
        // the third argument is called epsilon, which is maximum
        // distance from contour to approximated contour. It is
        // an accuracy parameter. A wise selection of epsilon is
        //needed to get the correct output.
        double epsilon = cv::arcLength(cv::Mat(contours[i]), true) * 0.1; // epsilon = 10% of arc length
        cv::approxPolyDP(
            cv::Mat(contours[i]),
            approx,
            epsilon,
            true
        );

        // Skip small or convex objects
        if (std::fabs(cv::contourArea(contours[i])) < 500 || cv::isContourConvex(approx))
            continue;

        drawContours(dst, contours, i, Scalar(255, 255, 255), CV_FILLED, 8, hierarchy, 0, Point());
    }

    imshow("contours", dst);

    // sum two images
    dst += bw;

    imshow("output", dst);

    waitKey(0);
    return 0;
}

of course you should play with the epsilon value in order to pick a value robust enough for all of your cases. Enjoy.