How can I select the best set of parameters in the Canny edge detection algorithm implemented in OpenCV?

Question

I am working with OpenCV on the Android platform. With the tremendous help from this community and techies, I am able to successfully detect a sheet out of the image.

<

Answer 1

You could calculate your thresholds using Otsu’s method.

The (Python) code would look like this:

high_thresh, thresh_im = cv2.threshold(im, 0, 255, cv2.THRESH_BINARY + cv2.THRESH_OTSU)
lowThresh = 0.5*high_thresh

Answer 2

Use the following snippet which I obtained from this blog:

v = np.median(gray_image)

#---- Apply automatic Canny edge detection using the computed median----
lower = int(max(0, (1.0 - sigma) * v))
upper = int(min(255, (1.0 + sigma) * v))
edged = cv2.Canny(gray_image, lower, upper)
cv2.imshow('Edges',edged)

So what am I doing here?

I am taking the median value of the gray scale image. The sigma value of 0.33 is chosen to set the lower and upper threshold. 0.33 value is generally used by statisticians for data science. So it is considered here as well.