All of the builds I've seen so far online have either red LED's around the cameras for lighting or white LEDs.Can someone explain pro's and con's of each setup for OpenPnP?
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Red is the complimentary color of green, and juju nozzles are green. The red light turns the green into a low contrast “grey”, which makes it easy to filter them out of the image when identifying components.While white leds work, they may take more effort to work well and/or reliably...There was a long thread here on this topic a month or so ago...John
On Tue, Jan 7, 2020 at 6:09 AM hardik <hardikp...@gmail.com> wrote:
All of the builds I've seen so far online have either red LED's around the cameras for lighting or white LEDs.Can someone explain pro's and con's of each setup for OpenPnP?--
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I also consider an experiment like that. But first I want to build a coaxial light housing then changing of the light plate will be very simple and good to observe the difference.
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Hi
For today's standard OpenPNP bottom vision pipeline it does not
matter either way.
BUT:
From an information theoretical standpoint and for future
improved and/or special case pipelines, with just red LEDs you
lose a lot of information. It's like just using the R channel of
your RGB camera, you lose two "dimensions" to distinguish object
from the background. A bit like closing one of your eyes and
seeing things only in 2D instead of 3D.
Here's one application that won't be possible with red LEDs:
https://github.com/openpnp/openpnp/pull/922
It is true, that this feature is only necessary for rare special
cases, but you might one day be glad to be able to do it.
This is even more true for the down-looking camera. I plan to
release a feeder that extensively uses the green screen effect and
this only works with RGB cameras and white lighting.
IMHO, red LEDs only make sense for physically monochrome cameras
and monochrome cameras nowadays only makes sense if you have a
hardware integrated hi-speed camera, because the sensor pixels are
larger and therefore faster, the image data is less and faster to
process. But immediately forget this with USB cameras or anything
cheap like it, the speed difference will not matter against
communication delays etc. and there are many much more promising
potentials for speed improvements in OpenPNP.
Personally, I would never go for red LEDs.
_Mark
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Hi
For today's standard OpenPNP bottom vision pipeline it does not matter either way.
BUT:
From an information theoretical standpoint and for future improved and/or special case pipelines, with just red LEDs you lose a lot of information. It's like just using the R channel of your RGB camera, you lose two "dimensions" to distinguish object from the background. A bit like closing one of your eyes and seeing things only in 2D instead of 3D.
Here's one application that won't be possible with red LEDs:
https://github.com/openpnp/openpnp/pull/922It is true, that this feature is only necessary for rare special cases, but you might one day be glad to be able to do it.
This is even more true for the down-looking camera. I plan to release a feeder that extensively uses the green screen effect and this only works with RGB cameras and white lighting.
IMHO, red LEDs only make sense for physically monochrome cameras and monochrome cameras nowadays only makes sense if you have a hardware integrated hi-speed camera, because the sensor pixels are larger and therefore faster, the image data is less and faster to process. But immediately forget this with USB cameras or anything cheap like it, the speed difference will not matter against communication delays etc. and there are many much more promising potentials for speed improvements in OpenPNP.
Personally, I would never go for red LEDs.
_Mark
Am 07.01.2020 um 18:04 schrieb John Plocher:
Red is the complimentary color of green, and juju nozzles are green. The red light turns the green into a low contrast “grey”, which makes it easy to filter them out of the image when identifying components.
While white leds work, they may take more effort to work well and/or reliably...
There was a long thread here on this topic a month or so ago...
John
On Tue, Jan 7, 2020 at 6:09 AM hardik <hardikp...@gmail.com> wrote:
All of the builds I've seen so far online have either red LED's around the cameras for lighting or white LEDs.Can someone explain pro's and con's of each setup for OpenPnP?--
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Hi Marek
the following will sound scoolmasterly, sorry, English is a
foreign language and it seems I can't express myself without
sounding like that :-}
Remember that what humans call "Color" is governed by what our
eyes can perceive. It happens, we have light sensitive receptors
for three wavelength ranges, the S, M, L cone cells.
While not directly corresponding to the Red, Green, Blue
wavelengths it seems our brain can differentiate these three basic
colors from the somewhat overlapping cone wavelength
sensitivities.
https://en.wikipedia.org/wiki/Color_vision#Physiology_of_color_perception
Btw. Bees see more wavelengths (e.g. ultraviolet), so this is
really only valid for our species.
Consequently what we call "white" is a "human perception of
sunlight" i.e. the R, G, B components all dialed up. A bee would
not call it "white" :-)
If we build color displays and cameras with RGB emitters/sensors,
these match that underlying model. But once the devices are built
on these assumptions, there is no way around it. All you can do is
communicate color in these three channels (I'm assuming affordable
consumer products here, but see P.S.).
If you have an RGB camera, it does really make no sense to
have red LEDs, because all you need to do to get the same
image with white light is to suppress the green and blue
channels in the image.
I did that with an image by Mike M.:


The same effect can probably be achieved in a pipeline by using
MaskHSV twice (suppress blue and green).
To answer your question: with these devices Fiducial recognition
simply cannot be better with colored
lighting!
I would instead look at better diffusion of the
light.
P.S. *) There might be one exception: Infrared. For technical
reasons, cameras are usually sensitive to infrared if you remove a
filter from it (some can be bought with the filter removed).
However I have no idea if infrared would be any better for
fiducial recognition. If this were the case, then it might make
sense to add infrared LEDs in addition to the
white light. Infrared might also be less susceptible to ambient
light changes.
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_Mark
P.S. *) There might be one exception: Infrared. For technical reasons, cameras are usually sensitive to infrared if you remove a filter from it (some can be bought with the filter removed). However I have no idea if infrared would be any better for fiducial recognition. If this were the case, then it might make sense to add infrared LEDs in addition to the white light. Infrared might also be less susceptible to ambient light changes.
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On Jan 10, 2020, at 4:27 AM, 'Kylra' via OpenPnP <ope...@googlegroups.com> wrote:
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So however you turn, your butt is still at the back?
(except for the concentric light that I still want to believe).
The concentric light is the best solution, of course. But a good
diffuser could get close. The idea is to make the black camera
"blind spot" as small as possible, so it will be small in the
reflection.
Imagine a LED ring behind it. Perhaps with some 90°-LEDs on the
inner ring edge also lighting the center.
As you see, the diffusor is quite "all around" or you could say "dome like" and the blind spot is
small in deed, the chances of it reflecting in the object/fiducial in a disruptive way are reduced (mehopes).
The 3D-printing layers result in a "natural" diffusion characteristic, the transparent PETG fibers act a bit like light conductors. It works very well with simulated LEDs behind it, quite even-looking. But I haven't had the time to integrate it into a mounting solution on my machine and do real camera shots yet.
It's a fully parametric OpenSCAD file, you can enter the camera
and lens data and it will calculate the perfect cone angle for the
funnel. The funnel is just outside the FOV cone. Preset for my ELP
6mm lens cameras.
If somebody is interested in this early untested stage, I can
provide the file.


Don't laugh, that's just hand-doodled :-D

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Don't laugh, that's just hand-doodled :-D
Am 10.01.2020 um 17:21 schrieb Marek T.:
--@Jim, are you able to upload some image of as poor HAL fidicial as you can find, and positioned exactly in the centre of FOV?
And I assume you don't have any cam transformations applied to the camera settings. If it is, an image is useless (telling not much).
@ Mark, I feel confused or worried about my "English" (I still haven't decided what more) :-("Imagine a LED ring behind it. Perhaps with some 90°-LEDs on the inner ring edge also lighting the center."So <behind> ( it sounds like meaning on the outer surface of your cloche) or on the <inner ring egde> (but which ring?) ?
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Don't laugh, that's just hand-doodled :-D
Am 10.01.2020 um 17:21 schrieb Marek T.:
--@Jim, are you able to upload some image of as poor HAL fidicial as you can find, and positioned exactly in the centre of FOV?
And I assume you don't have any cam transformations applied to the camera settings. If it is, an image is useless (telling not much).
@ Mark, I feel confused or worried about my "English" (I still haven't decided what more) :-("Imagine a LED ring behind it. Perhaps with some 90°-LEDs on the inner ring edge also lighting the center."So <behind> ( it sounds like meaning on the outer surface of your cloche) or on the <inner ring egde> (but which ring?) ?
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@Jim, are you able to upload some image of as poor HAL fidicial as you can find, and positioned exactly in the centre of FOV?And I assume you don't have any cam transformations applied to the camera settings. If it is, an image is useless (telling not much).


Has anyone looked at use of UV/IR cut filters then a color bandpass filter?That would cut out allot of un-needed light getting to the camera.

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Instead of an out of focus image, add a Gaussian blur stage to your pipeline. Does the same thing and is very common in vision operations.Jason
On Sat, Jan 11, 2020 at 11:36 AM Mike M. <mike...@gmail.com> wrote:
--Based on my experiance sometimes it helps that image is a bit out of focus - than for vision you have less adjustments to make for pipline to get out right shape of element you are katching.Mike
On Saturday, 11 January 2020 17:46:38 UTC+1, my 3DCNCPNP wrote:Marek. Attached is Hot Air Leveled fiducial pipeline debug output with my Keyence CA-DXR3. (bought used from ebay)My ELP cam is a little out of focus.I put a 1206 for size reference.I have tried a few different lighting setups and this is the best one so far.I used to polish my fiducials with a white Staedtler eraser and that worked quite well even with bad lighting.Peter
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