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I work with the segmentation of simulated rock pile images. My input image is a depth image(given below). I tried to apply the canny edge but it doesn't give promising results - rock pile areas which are clustered together are detected as a single large rock, edges abruptly end.

Since a depth image of a rock pile has low changes in intensity, am I right in saying that the canny edge is not appropriate for this purpose?

I have applied the adaptive thresholding operation, it seems to show better results because it does not really work with the gradient but with average intensity values of the neighborhood. The image is given below.

The actual simulated scene

enter image description here

The depth image

enter image description here

The result of canny edge

enter image description here

Adaptive thresholding result

enter image description here

VM4
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  • IMO no edge detector will do much better than Canny. Low contrast edge detection is difficult and in this case, seems hopeless. But what exactly are you trying to do with edge detection ? Possibly an XY problem. –  Oct 23 '19 at 07:51
  • But the adaptive threshold operation shows better results in this case. How so? – VM4 Oct 24 '19 at 08:47
  • "better" is subjective. Without more context, no answer is possible. –  Oct 24 '19 at 16:06

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