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Ask HN: How to handle images resistant to edge detection?

1 点作者 TrackerLounge将近 5 年前
What tools or techniques have you found useful to detect objects, that are resistant to edge detection, during image processing for computer vision workflows?<p>Where one object bleeds into the other gradually.<p>Two examples of this include:<p>1. Close image of Foot prints in beach sand - edge detection focus on the edges of individual grains of sand rather than the gradient edge of the track.<p>For an example see: https:&#x2F;&#x2F;github.com&#x2F;TrackerLounge&#x2F;TrackingAndComputerVision - second image.<p>2. A halibut (fish) half in and half out of plankton-rich partially reflective water. The color of the fish and water can be so close that it becomes very difficult to programmatically detect where one ends and the other begins.<p>3. Cryptic sea creatures (e.g. mussels, clam, flatfish, etc.) half-buried in mud on sea floor.<p>I run into this question in image processing everywhere I look.<p>In these &quot;gradient edge&quot; scenarios what have you found to work best?

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