Opencv - Ellipse Contour Not fitting correctly - python-3.x

Question

I want to draw contours around the concentric ellipses shown in the image appended below. I am not getting the expected result.
I have tried the following steps:
Read the Image
Convert Image to Grayscale.
Apply GaussianBlur
Get the Canny edges
Draw the ellipse contour
Here is the Source code:
import cv2
target=cv2.imread('./source image.png')
targetgs = cv2.cvtColor(target,cv2.COLOR_BGRA2GRAY)
targetGaussianBlurGreyScale=cv2.GaussianBlur(targetgs,(3,3),0)
canny=cv2.Canny(targetGaussianBlurGreyScale,30,90)
kernel=cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (3, 3))
close=cv2.morphologyEx(canny,cv2.MORPH_CLOSE,kernel)
_,contours,_=cv2.findContours(close,cv2.RETR_TREE,cv2.CHAIN_APPROX_NONE)
if len(contours) != 0:
for c in contours:
if len(c) >= 50:
hull=cv2.convexHull(c)
cv2.ellipse(target,cv2.fitEllipse(hull),(0,255,0),2)
cv2.imshow('mask',target)
cv2.waitKey(0)
cv2.destroyAllWindows()
The image below shows the Expected & Actual result:
Source Image:

Answer 1

Algorithm can be simple:
Convert RGB to HSV, split and working with a V channel.
Threshold for delete all color lines.
HoughLinesP for delete non color lines.
dilate + erosion for close holes in ellipses.
findContours + fitEllipse.
Result:
With new image (added black curve) my approach do not works. It seems that you need to use Hough ellipse detection instead "findContours + fitEllipse".
OpenCV don't have implementation but you can find it here or here.
If you don't afraid C++ code (for OpenCV library C++ is more expressive) then:
cv::Mat rgbImg = cv::imread("sqOOE.jpg", cv::IMREAD_COLOR);
cv::Mat hsvImg;
cv::cvtColor(rgbImg, hsvImg, cv::COLOR_BGR2HSV);
std::vector<cv::Mat> chans;
cv::split(hsvImg, chans);
cv::threshold(255 - chans[2], chans[2], 200, 255, cv::THRESH_BINARY);
std::vector<cv::Vec4i> linesP;
cv::HoughLinesP(chans[2], linesP, 1, CV_PI/180, 50, chans[2].rows / 4, 10);
for (auto l : linesP)
{
cv::line(chans[2], cv::Point(l[0], l[1]), cv::Point(l[2], l[3]), cv::Scalar::all(0), 3, cv::LINE_AA);
}
cv::dilate(chans[2], chans[2], cv::getStructuringElement(cv::MORPH_RECT, cv::Size(3, 3)), cv::Point(-1, -1), 4);
cv::erode(chans[2], chans[2], cv::getStructuringElement(cv::MORPH_RECT, cv::Size(3, 3)), cv::Point(-1, -1), 3);
std::vector<std::vector<cv::Point> > contours;
std::vector<cv::Vec4i> hierarchy;
cv::findContours(chans[2], contours, hierarchy, cv::RETR_TREE, cv::CHAIN_APPROX_SIMPLE);
for (size_t i = 0; i < contours.size(); i++)
{
if (contours[i].size() > 4)
{
cv::ellipse(rgbImg, cv::fitEllipse(contours[i]), cv::Scalar(255, 0, 255), 2);
}
}
cv::imshow("rgbImg", rgbImg);
cv::waitKey(0);