finding bounding box of centroid with limited information - object-detection

Question

I have detected blob keypoints in opencv c++. The centroid displays fine. How do I then draw a bounding box around the detected blob if I only have the blob center coordinates? I can't work backwards from center because of too many unknowns(or so I believe).
threshold(imageUndistorted, binary_image, 30, 255, THRESH_BINARY);
Ptr<SimpleBlobDetector> detector = SimpleBlobDetector::create(params);
// Detect blob
detector->detect(binary_image, binary_keypoints);
drawKeypoints(binary_image, binary_keypoints, bin_image_keypoints, Scalar(0, 0, 255), DrawMatchesFlags::DRAW_RICH_KEYPOINTS);
//draw BBox ?
What am I overlooking to draw the bounding box around the single blob?

Answer 1

I said:
I can't work backwards from center because of too many unknowns(or so I believe).
There is not limited information if blob size is used: keypoints.size which returns the diameter of the blob in question. Though there might be some inaccurate results with highly asymmetric or lopsided targets, this worked well for me b/c I used spheroid objects. Moments/ is probably the better approached for the asymmetrical targets.
keypoints.size should not be confused with keypoints.size(). The latter does a count in the vector of objects in my case the former is the diameter. Using both.
Using the diameter I can then calculate the rest with no problem:
float TLx = (ctr_x - r);
float TLy = (ctr_y - r);
float BRx = (ctr_x + r);
float Bry = (ctr_y + r);
Point TLp(TLx-10, TLy-10); //works fine without but more visible with enhancement
Point BRp(BRx+10, Bry+10); //same here
std::cout << "Top Left: " << TLp << std::endl << "Right Lower:" << BRp << std::endl;
cv::rectangle(bin_with_keypoints, TLp, BRp, cv::Scalar(0, 255, 0));
imshow("With Green Bounding Box:", bin_with_keypoints);
TLp = top left point with 10px adjustments to make box bigger.
BRp = bottom right point
TLx, TLy are calculated from blob center coordinates as well as BRps. If you are going to use multiple targets would suggest contours approach (with the moments). I have 1 - 2 blobs to keep track of which is a lot easier but keeps resource usage down.
Rectangle drawing function can also work with Rect (diameter = keypoint.size)
Rect r(TLp, BRp, center_x + diameter/2, center_y+diamter/2) // r(TLc, BRc, width, heigth)
cv::rectangle(bin_with_keypoints, rect, cv::Scalar(0, 255, 0));