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Found 3 results

  1. Hello, I am having a bit of an issue applying a threshold to an image and getting reliable results. I am thinking using edge detection prior to doing any other image processing could make this work... but I am at a loss for how to implement it. If you look at the image below you will see the root of my problem. The top set of images and bottom are only a second or 2 apart but the threshold sees them differently, yet the edge detection seems to correctly detect the edges the same. I only care about the range of pixels that usually makes up the brightest part of the image (hence the thresholding) but the low end of that range changes from frame to frame and I am left with an incorrect determination. My question is, does anyone know of a good way to use edge detection (or maybe some other method that I am not aware of) to help me with this problem?
  2. Version 1.0

    146 downloads

    The Threshold Hysteresis VI allows an input (for example, a sensor) to drift out of an inner limit without generating an invalid flag, but if it drifts outside an outer limit it then becomes invalid. For the reverse, when the input crosses back into the outer limit it remains invalid until the value falls inside the inner limit. For simplicity, only one input parameter is provided for both the inner & outer limits, and is negated for the lower limit, as generally tolerance limits are equidistant from the nominal.
  3. Name: Deon Bester Submitter: Deon Submitted: 06 Nov 2014 Category: *Uncertified* LabVIEW Version: 8.6.1 License Type: BSD (Most common) Sexiest threshold hysteresis VI on the web! Click here to download this file
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