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c++ - OpenCV's fitEllipse() sometimes returns completely wrong ellipses

My goal is to recognize all the shapes present in an image. The idea is:

  1. Extract contours
  2. Fit each contour with different shapes
  3. The correct shape should be the one with area closest to the contour's area.

Example image: enter image description here

I use fitEllipse() to find the best fit ellipse to the contours, but the result is a bit messy: enter image description here

The likely-correct ellipses are filled with blue, and the bounding ellipses are yellow. The likely-incorrect contours are filled with green, and the (wrong) bounding ellipses are cyan.

As you can see, the ellipse bounding the triangle in the first row looks pretty good for the best fit. The bounding ellipse of the triangle in the third row doesn't seem to be the best fit, but still acceptable as a criteria for rejecting an incorrect ellipse.

But I can't understand why the remaining triangles have bounding ellipse completely outside their contour. And the worst case is the third triangle in the last row: The ellipse is completely wrong but it happens to have the area close to the contour's area, so the triangle is wrongly recognized as an ellipse.

Do I miss anything? My code:

#include <iostream>
#include <opencv/cv.h>
#include <opencv/highgui.h>

using namespace std;
using namespace cv;

void getEllipses(vector<vector<Point> >& contours, vector<RotatedRect>& ellipses) {
    ellipses.clear();
    Mat img(Size(800,500), CV_8UC3);
    for (unsigned i = 0; i<contours.size(); i++) {
        if (contours[i].size() >= 5) {
            RotatedRect temp = fitEllipse(Mat(contours[i]));
            if (area(temp) <= 1.1 * contourArea(contours[i])) {
                //cout << area(temp) << " < 1.1* " << contourArea(contours[i]) << endl;
                ellipses.push_back(temp);
                drawContours(img, contours, i, Scalar(255,0,0), -1, 8);
                ellipse(img, temp, Scalar(0,255,255), 2, 8);
                imshow("Ellipses", img);
                waitKey();
            } else {
                //cout << "Reject ellipse " << i << endl;
                drawContours(img, contours, i, Scalar(0,255,0), -1, 8);
                ellipse(img, temp, Scalar(255,255,0), 2, 8);
                imshow("Ellipses", img);
                waitKey();
            }
        }
    }
}

int main() {
    Mat img = imread("image.png", CV_8UC1);
    threshold(img, img, 127,255,CV_THRESH_BINARY);
    vector<vector<Point> > contours;
    vector<Vec4i> hierarchy;
    findContours(img, contours, hierarchy, CV_RETR_EXTERNAL, CV_CHAIN_APPROX_SIMPLE);
    vector<RotatedRect> ellipses;
    getEllipses(contours, ellipses);
    return 0;
}
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Keep in mind, that fitEllipse is not the computation of a boundingEllipse but a least square optimization that assumes the points to lie on an ellipse.

I can't tell you why it fails on the 3 triangles in the last row so badly but "works" on the triangle one line above, but one thing I've seen is, that all 3 triangles in the last row were fitted to a rotatedRect with angle 0. Probably the least square fitting just failed there.

But I don't know whether there is a bug in the openCV implementation, or wether the algorithm can't handle those cases. This algorithm is used: http://www.bmva.org/bmvc/1995/bmvc-95-050.pdf

My advice is, to only use fitEllipse if you are quite sure that the points really belong to an ellipse. You wont either assume to get reasonable results from fitLine if you have random data points. Other functions you might want to look at are: minAreaRect and minEnclosingCircle

if you use RotatedRect temp = minAreaRect(Mat(contours[i])); instead of fitEllipse you will get an image like this:

enter image description here

maybe you can even use both methods and refuse all ellipses that fail in both versions and accept all that are accepted in both versions, but investigate further in the ones that differ?!?


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