Detecting the vision target

[biojae]

Originally Posted by Greg McKaskle

The LV installation contains a new example for rectangular image processing. Additionally, there should soon be a white paper posted to the NI site that will explain a few approaches.

The most obvious approach is to use the rectangle fit function, but it is quite picky, expecting angles to be quite close to 90 degrees and lines to be quite straight. Distortion due to lens and position easily cause the rectangle definition to fail its requirements.

The example in LV is particle based, and scores the particles for rectangularity, aspect ratio, and edge strength. If they score above the limits, the position and distance are calculated.

Is this example in the other languages? (C++, Java)
I don't have the software installed and updated yet.

If the paper doesn't make it up soon, I'll be happy to answer other questions.

Greg McKaskle

Thank you very much.

EDIT:
Does the example depend on the lighting source being a certain color?
and does the distance calculation account for which target is seen (I would assume that it doesn't)?

[Ginto8]

If your software guys are up for some heavy image processing, they can use the resources linked by davidthefat in this thread. They describe the Hough algorithm, which constructs a polygon from a series of points in an image. If you use an algorithm that can construct a polygon instead of looking for an ellipse or rectangle, you don't have to worry as much about perspective distortion affecting detection, because even if you're at an angle that makes the vision target look like a parallelogram instead of a rectangle, the algorithm will be able to tell that it's there.

[jhersh]

Originally Posted by biojae

Is this example in the other languages? (C++, Java)
I don't have the software installed and updated yet.

The new vision example has not yet been ported to java or c++.

Joe