How do I match the levels of hundreds of photos with a 90% white background?

I assume this would be a common question for product photography, but I’ve spent multiple days searching various sites for a solution to automate this simple task, but found nothing.

Lets say there are 200 photos taken in controlled lighting with the identical camera settings (exposure, white balance etc. all manually set), but there is a barely evident color cast and exposure difference.

I have been correcting this manually so far. Using eyedropper to average an area from the white background, using levels or curves to get the RGB numbers to 230 (relative 90% white).

To output 255 at 247 for example. Almost all the photos have min difference in average level +/-3 values. So in order to get a perfect print each of the images have to be opened separately and the settings dialled in depending on the conditions.

I’m thinking that there has to be a way to automate this, since the white area is always in the same place for the photos and the process is very routine.

I’ve tried the Match Total Exposure in Lightroom, but that only sets an amount based on camera settings. Nothing changes, if the settings were the same on all the images.

I tried setting a certain exposure on 1 photo and syncing it to all the rest. That just copy-pastes the +0.5 value to all the photos, so some are still brighter than others.

Then I moved to photoshop and tested the “Auto Color corrections”. Either monochromatic or dark&light. There does not seem to be a predictable way for it to function. On some images it does go from 225 to 230 and then on the next it goes from 226 to 218. I guess the second photo might have tiny highlights that force the background average to darken?

Then I was hoping to run a bulk action that asks for the user to just input the white level using the eyedropper for each photo, but can’t wrap my head around even that. I guess I’m burnt out at this point and will just manually do this.

If anyone has the patience to read this and help out I would be thankful.


Source : Link , Question Author : mku , Answer Author : Community

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