I’ve successfully done something like this in the past for an entirely different reason. You’ll probably need someone who can code to package this up and loop through your drive, but the approach I took was:

Convert all images to smallish sizes such as 800x600 or even somewhat smaller.

Convert small images to Black and white with low dynamic range: 4, 2 or even 1 bit per pixel.

I used “ImageMagick” to do the above, but the tool doesn’t matter.

Now run a Fuzzy Hash against all the images.

I’ve used both “ssdeep” and “deeptoad” to produce match scores.

The concept behind it is that by first converting all images to small poor quality variants, you eliminate subtle changes you do not want to be factors. The smaller size also reduces fuzzy hashing processing loads substantially.

The fuzzy hashing scores attempt to evaluate degrees of match.

You may have to play with the parameters to find ones that work acceptably for you.

Note that the "ssdeep" user guide gives an example of comparing segments of videos to reference videos. This may be closer to what you want, but I' not sure.

Good luck!