Runtime error Visual Studio and OpenCV Error while using SURF

Question

The following code is supposed to perform feature detection using SURF in OpenCV2.3 on Visual Studio 2010. The image "sample.jpg" is a coloured image (RGB) of a book and the video captured will consist of several different books. There is no compile error but on CTRL F5, the console says Native' has exited with code -1073741811 (0xc000000d). This is strange because other programs were working fine. I tested it by deleting this feature detection code with a simple code that displays an image, and that seems to be working fine. Only when I run this code, it throws this error. I have included the following library under Additional dependencies :

opencv_core230d.lib
opencv_highgui230d.lib
opencv_ml230d.lib
opencv_legacy230d.lib
opencv_imgproc230d.lib
opencv_features2d230d.lib
opencv_calib3d230d.lib
opencv_flann230d.lib

Do I need to include a library or something for SURF as this is the first time I am working with Surf. Kindly help.

int main()
{
    Mat object = imread( "C:\\OpenCV2.3\\sample.jpg");

    if( !object.data )
    {
        std::cout<< "Error reading object " << std::endl;
        return -1;
    }

    //Detect the keypoints using SURF Detector
    int minHessian = 500;

    SurfFeatureDetector detector( minHessian );
    std::vector<KeyPoint> kp_object;

    detector.detect( object, kp_object );

    //Calculate descriptors (feature vectors)
    SurfDescriptorExtractor extractor;
    Mat des_object;

    extractor.compute( object, kp_object, des_object );

    FlannBasedMatcher matcher;

    VideoCapture cap(0);
if( !cap.isOpened() ) return -1;

    namedWindow("Good Matches");

    std::vector<Point2f> obj_corners(4);

    //Get the corners from the object
    obj_corners[0] = cvPoint(0,0);
    obj_corners[1] = cvPoint( object.cols, 0 );
    obj_corners[2] = cvPoint( object.cols, object.rows );
    obj_corners[3] = cvPoint( 0, object.rows );

    char key = 'a';
    int framecount = 0;
    while (key != 27)
    {
        Mat frame;
        cap >> frame;

        if (framecount < 5)
        {
            framecount++;
            continue;
        }

        Mat des_image, img_matches;
        std::vector<KeyPoint> kp_image;
        std::vector<vector<DMatch > > matches;
        std::vector<DMatch > good_matches;
        std::vector<Point2f> obj;
        std::vector<Point2f> scene;
        std::vector<Point2f> scene_corners(4);
        Mat H;
        Mat image;

        cvtColor(frame, image, CV_RGB2GRAY);

        detector.detect( image, kp_image );
        extractor.compute( image, kp_image, des_image );

        matcher.knnMatch(des_object, des_image, matches, 2);

        for(int i = 0; i < min(des_image.rows-1,(int) matches.size()); i++) //THIS LOOP IS SENSITIVE TO SEGFAULTS
        {
            if((matches[i][0].distance < 0.6*(matches[i][3].distance)) && ((int) matches[i].size()<=2 && (int) matches[i].size()>0))
            {
                good_matches.push_back(matches[i][0]);
            }
        }

        //Draw only "good" matches
        drawMatches( object, kp_object, image, kp_image, good_matches, img_matches, Scalar::all(-1), Scalar::all(-1), vector<char>(), DrawMatchesFlags::NOT_DRAW_SINGLE_POINTS );

        if (good_matches.size() >= 4)
        {
            for( int i = 0; i < good_matches.size(); i++ )
            {
                //Get the keypoints from the good matches
                obj.push_back( kp_object[ good_matches[i].queryIdx ].pt );
                scene.push_back( kp_image[ good_matches[i].trainIdx ].pt );
            }

            H = findHomography( obj, scene, CV_RANSAC );

            perspectiveTransform( obj_corners, scene_corners, H);

            //Draw lines between the corners (the mapped object in the scene image )
            line( img_matches, scene_corners[0] + Point2f( object.cols, 0), scene_corners[1] + Point2f( object.cols, 0), Scalar(0, 255, 0), 4 );
            line( img_matches, scene_corners[1] + Point2f( object.cols, 0), scene_corners[2] + Point2f( object.cols, 0), Scalar( 0, 255, 0), 4 );
            line( img_matches, scene_corners[2] + Point2f( object.cols, 0), scene_corners[3] + Point2f( object.cols, 0), Scalar( 0, 255, 0), 4 );
            line( img_matches, scene_corners[3] + Point2f( object.cols, 0), scene_corners[0] + Point2f( object.cols, 0), Scalar( 0, 255, 0), 4 );
        }

        //Show detected matches
        imshow( "Good Matches", img_matches );

        key = waitKey(1);
    }
    return 0;
}

Answer 1

I believe the SURF detector doesn't work on color images. You will need to load them in grayscale using

Mat object = imread( "C:\\OpenCV2.3\\sample.jpg",CV_LOAD_IMAGE_GRAYSCALE);