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2016-01-04 09:29:51 -0600	answered a question	Missing/double edges in OpenCV/scikit-image implementations of Canny edge detector Answer is already in the comments, it works with an aperture of 5. I also submitted an issue.
2016-01-01 10:18:23 -0600	commented question	Missing/double edges in OpenCV/scikit-image implementations of Canny edge detector Using an aperture size of 5 works in this case. However, I can't answer my own question yet.
2016-01-01 09:06:31 -0600	commented question	Missing/double edges in OpenCV/scikit-image implementations of Canny edge detector Yeah true the donut is not binary, don't think it should make a difference, though.
2016-01-01 08:54:08 -0600	commented question	Missing/double edges in OpenCV/scikit-image implementations of Canny edge detector Thanks for the suggestions! The images are all png already...
2016-01-01 08:23:12 -0600	received badge	● Student (source)
2015-12-31 08:19:05 -0600	asked a question	Missing/double edges in OpenCV/scikit-image implementations of Canny edge detector If found that the Canny edge detector in OpenCV (2.4.9 on OSX via brew), applied on the binary test image below (left), misses an edge segment at the upper right corner (middle). For comparison I tried scikit-image (right), which produces a small hole at the top (can be fixed using different parameters) and double edges (which should not happend according to my understanding of the algorithm). I tried different parameters with no effect, probably because the input image is already a binary image. Code: `# opencv canny=cv2.Canny(image,300,500) # scikit-image canny = img_as_ubyte(feature.canny(image, 1, 300, 500))` Is this expected behaviour? Anything I can do to prevent those gaps?