There’s lots of advice online about sensors and pixel sizes and so on, but one of the best tips I’ve seen in a while is on the Adimec blog.
The accurately-but-not-very-concisely-titled, “Evaluating Machine Vision Cameras versus Comparing Camera Specification Documents” talks about measuring the photon transfer curve, which sounds like hard work, but what it boils down to is this: choose the camera that works best in your application.
Easy to say, I know, but what I believe Adimec are getting at is that the camera is just part of a system. That system includes the lighting, the enclosure, the lens, and of course, the object you’re looking at. So you put the camera in that environment and find out how well it works.
Now as a good engineer, you want to evaluate performance on the basis of measurable criteria. But I think many machine vision people, (myself included,) have a tendency to look at a pair of images from two different cameras and pick the one that “looks” best. And this is where the photon transfer curve comes in to play.
I’m not going to regurgitate all the info about this that’s already on the Adimec website – use the link above and you’ll find it all – but I do urge you to learn more and figure out how to use it. Or if you want to go to the source, look through my list of “Friends” and go to Harvest Imaging
Maybe it is more work, but it gives you data as a basis for selecting your camera. Or just go with the vendor that offers the best freebies.