I'd assumed you'd need something more like: http://cmm.ensmp.fr/~beucher/prom_sta.html[^] As you can see the lanes on the road form "Trapezoids" which can be detected, this doesn't help you, as you have a very different problem.
sebogawa wrote:
I just think distancing and angling every white point on the image would be very time consuming processing wise.
Yes, but complicated tasks such as these are heavy-duty! One thing that strikes me immediately is that you should look at your camera/image resolution, it doesn't need to be very high and this will drastically cut down your processing costs. Assuming the surface is flatish and the camera is at a constant height and angle, you can calculate the distance of every pixel in the image when the rig is calibrated (i.e. once) as each will always appear at the same distance due to the geometry being constant. Again, at calibration, you then create an ordered (by distance) dictionary of pixel co-ordinates. When you start in earnest it is just a matter of rattling through the image to find the nearest white pixel. Triaging the areas in the image into "Don't worry- too far away", "need to start planning", "urgent" could again reduce your costs. Things that could complicate this are a) obstacles being mistaken for lines (if they are white) b) The robot heading off in the wrong direction! Keep us informed as this sort of thing is interesting!!!!
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