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" Code number is S.C.F.O.S. # (Note that code number does not match Cover Thumbnail for Four Color (Dell, series) # - Santa Claus.
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Maybe you will find an answer to your question amongst our pamphlets and brochures more Newspapers And Magazines Maybe you are not as unlucky as your plates suggest. Here is a great new section of the best we can find in Public Domain magazines and newspapers more The blue and green channels are all okay. If in any of the channels, any of the chips are all , then color correction with this algorithm will fail just as you're observing. Below is an example of what I did to inspect your target image and note how the min and max of the red chip are both I suspect that since the red channel is over-exposed, simply dropping the chips that are saturated won't be a working solution but it may be worth a shot just to see what happens.
Thank you both for the help nfahlgren jberry Both responses were very useful, I shall have a go with dropping the fully saturated chips and report back my findings. I'm assuming this is something that can only be fixed with changing settings on my camera. Do you have any recommendations for camera settings that would alleviate this? Otherwise, I will just fiddle with the settings until I get something that is not fully saturated. Happy to help JLJ90!
The first setting I would locate on your camera is the "exposure compensation" and play with that first. This feature will under or over expose an image based on ISO step units. Otherwise you can switch your camera to full manual and individually adjust the gains of each RGB channel but this is not very fun or intuitive.
Hello, I have recently been trying to continue with this, I have used the method linked in the notebook nfahlgren linked. I had the raw files for the images so I changed the images so that the red chips were not fully saturated. However, I have come across a new issue, and am not entirely sure what the error message is saying. The input images are different sizes, but I don't understand why that should make a difference, when trying to correct for color?
I have checked the images and the mask definetly line up with the colour chips, so that is no longer an issue. Hi JLJ90 , the issue is only with the "debug" image output.
It's because we are using np. Horizontally stacking the images requires them to be the same size though, so that broke an assumption of ours. To get around this you can set pcv. To visualize the corrected image you can use pcv. I'll have to think about how to get around the issue. We could either stop using np. If that's helpful at some point. The images were quite close to start with, w. From the output I have shown, would this be expected behaviour?
I am not sure if I have the theory behind this correct, but I was assuming the values would be closer, not further to the target.
Hi JLJ90 I ran the correction as well and got a very similar image to what you've produced. This is the standardized source image. One major problem with color correction is spotlight effect. This effect is more prominent in close up shots such as the ones you're taking.
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I've done a couple tests in ImageJ to detect this effect and I believe you have a small amount of it. The new window shows the x-position of the ROI on the xaxis and the average gray value on the yaxis. If the line is not flat, you have some amount of spotlight effect. When doing color correction, this spotlight effect has to be perfectly identical between source to target. I used plot profile on your source and target images and I found that there are differing slopes between them.
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We know that spotlight effect is a problem and unfortunately we don't have a solution just yet. There are algorithms out there that correct for spotlight effect so in the future that will certainly be a priority to manage. In the meantime, you might want to consider ways to limit non-uniform lighting in your images. Two great ways that I've used is to invest in a good light diffuser and not being too close to objects in the scene when taking the picture.
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Right now you are very very close to having the same light conditions between your source and target so I imagine that a small change to your imaging methods would be enough to fix the problem. I have never seen this phenomenon before, thanks for pointing it out. I'm assuming the image gets brighter in certain regions which affect the grey colour. I can understand how a light diffuser would work, but do you have any insight as to why distance to image alters the effect? Hi JLJ90 sorry for the delay in getting back to you. You are exactly correct about how non-uniform light effects the gray values of the RGB values of the color checker.
If one side is more illuminated then the regression method used in the correction will be very biased and produce artificial colors like what we're observing. I did notice that you were able to adjust the overall brightness in the second source image you provided. I checked all your chips and they look great in every channel.
Light diffusers are great for turning "hard" light into "soft" light. So the further the light source and camera are from the objects, the softer and more uniform the lighting is across your scene. That's why I've found that if you can get the camera a little further away than expected, color correction performs as it should. And thanks for the suggestion to get a document together addressing all these issues. It would be very helpful for many people if something was created to bypass these issues before they occur.
There is an example of a "good" and "problematic" result in the color correction tutorial. Hopefully this tool will allow PlantCV users to test lighting conditions and camera settings to ensure color correction will work properly on their dataset. Please feel free to reopen this issue with other comments or questions regarding color correction! Skip to content. Dismiss Track tasks and feature requests Join 40 million developers who use GitHub issues to help identify, assign, and keep track of the features and bug fixes your projects need.
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