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I want to improve the speed of cv::matchTemplate by following the image pyramid approach which was tried here and presented on the linked page which is currently down but can be seen via google-cache:

My problem is that the C++ implementation visible in google-cache crashes for specific image sizes. I'm on Ubuntu 14.04.3 LTS 64 bit and see the crash on both newest versions of OpenCV 2.4.11 and 3.1.0. I created a working (=crashing) implementation which is very close to the linked tutorial. These are the example images that cause the crash: reference.png, template.png.

reference.png is 145 x 128 and template.png is 24 x 47
The line causing the problem is: ref(r + (tpl.size() - cv::Size(1,1)))
It seems like the created ROI is 1 pixel too big but I don't know how to fix this correctly or if I'm doing something wrong. Many thanks for any hint!

// main.cpp:
#include <opencv2/imgproc/imgproc.hpp>
#include <opencv2/highgui/highgui.hpp>
#include <iostream>

/**
 * Function to perform fast template matching with image pyramid
 */
void fastMatchTemplate(cv::Mat& srca,  // The reference image
                   cv::Mat& srcb,  // The template image
                   cv::Mat& dst,   // Template matching result
                   int maxlevel)   // Number of levels
{
    std::vector<cv::Mat> refs, tpls, results;

    // Build Gaussian pyramid
    cv::buildPyramid(srca, refs, maxlevel);
    cv::buildPyramid(srcb, tpls, maxlevel);

    cv::Mat ref, tpl, res;

    // Process each level
    for (int level = maxlevel; level >= 0; level--)
    {
        ref = refs[level];
        tpl = tpls[level];
        res = cv::Mat::zeros(ref.size() + cv::Size(1,1) - tpl.size(), CV_32FC1);

        if (level == maxlevel)
        {
            // On the smallest level, just perform regular template matching
            cv::matchTemplate(ref, tpl, res, CV_TM_CCORR_NORMED);
        }
        else
        {
            // On the next layers, template matching is performed on pre-defined
            // ROI areas.  We define the ROI using the template matching result
            // from the previous layer.

            cv::Mat mask;
            cv::pyrUp(results.back(), mask);

            cv::Mat mask8u;
            mask.convertTo(mask8u, CV_8U);

            // Find matches from previous layer
            std::vector<std::vector<cv::Point> > contours;
            cv::findContours(mask8u, contours, CV_RETR_EXTERNAL, CV_CHAIN_APPROX_NONE);

            // Use the contours to define region of interest and
            // perform template matching on the areas
            for (size_t i = 0; i < contours.size(); i++)
            {
                cv::Rect r = cv::boundingRect(contours[i]);

                // This is the problem which leads to the crash if not catched here:
                cv::Rect roi = r + (tpl.size() - cv::Size(1,1));
                assert(roi.x + roi.width <= ref.cols);

                try
                {
                    cv::matchTemplate(
                        ref(r + (tpl.size() - cv::Size(1,1))),
                        tpl,
                        res(r),
                        CV_TM_CCORR_NORMED
                    );
                }
                catch (...)
                {
                    std::cerr << "EXCEPTION!" << std::endl;
                }
            }
        }

        // Only keep good matches
        cv::threshold(res, res, 0.94, 1., CV_THRESH_TOZERO);
        results.push_back(res);
    }

    res.copyTo(dst);
}

int main()
{
    cv::Mat ref = cv::imread("reference.png"); // 145 x 128
    cv::Mat tpl = cv::imread("template.png"); // 24 x 47
    if (ref.empty() || tpl.empty())
        return -1;

    cv::Mat ref_gray, tpl_gray;
    cv::cvtColor(ref, ref_gray, CV_BGR2GRAY);
    cv::cvtColor(tpl, tpl_gray, CV_BGR2GRAY);

    cv::Mat dst;
    fastMatchTemplate(ref_gray, tpl_gray, dst, 2);

    cv::waitKey();
    return 0;
}