What is calibration target accuracy?
When we talk about calibration target accuracy, we’re really asking one basic question: “How perfect is this pattern?” Just like when you buy a ruler, you want to make sure the measurements are correct. A calibration target works the same way – it needs to be extremely precise for your camera to work properly.
There are two main ways we check if a calibration target is accurate enough. The first is called feature position accuracy, which is basically asking “Are all the dots or squares in exactly the right spots?” Think of it like this: imagine you drew a perfect grid on a piece of paper with a computer, then tried to print it out. Position accuracy tells you how close your printed version is to that perfect computer drawing. If some dots ended up a little too far left or right, or up or down, that would show up as poor position accuracy.
The second type is feature spacing accuracy, which asks a different question: “Are all the gaps between neighboring dots exactly the same size?” Picture a fence with evenly spaced posts. Even if each post is in roughly the right area, you’d still want the distance between post 1 and post 2 to be exactly the same as the distance between post 2 and post 3. That’s what spacing accuracy measures – the consistency of those gaps between features.
Both types of accuracy matter because they affect different things. If the overall positions are wrong, your entire measurement system will be shifted or twisted. If the spacing between features isn’t consistent, your measurements might be correct in some areas but wrong in others. It’s like having a ruler where the first few inches are accurate, but then the spacing gets gradually more compressed toward the end.
For anyone using machine vision or camera calibration systems, understanding these two accuracy types helps explain why some calibration targets cost more than others. A cheap target might look fine to your eyes, but when a computer tries to use it for precise measurements, those tiny position and spacing errors add up quickly. That’s why professional applications require targets with accuracy measured in microns – because even the smallest imperfections can throw off an entire measurement system.
