Vignetting is the shading of the image towards the edges. It interferes with many image processing algorithms, affecting measurement results, edge detection and object recognition.
Algorithms based on binary images, such as blob tools, are particularly affected by this optical error.
Artificial vignetting
Artificial vignetting occurs when the maximum possible light path of the lens is mechanically restricted, for example by the edge of the body, the lens mount or the filter holder.
It is very easy to detect: Hold the lens at a slight angle and look through it. The effective aperture through the lens narrows to an almond shape, and the adjacent non-transparent areas shadow the image.
This error can be reduced by stopping down the lens, as the light rays near the edges that cause the error can no longer pass through the lens system.
Creation of vignetting
Natural illumination falloff (vignetting)
Physical laws also cause a natural fall-off at the edges. The decrease in brightness is proportional to the fourth power of the image angle. This error cannot be corrected by stopping down.
The smaller the camera's sensor, the easier it is to make lenses with low peripheral light fall-off.
Important for Machine Vision
Slightly stop down the optics.
User enhancement: downstream software correction (shading correction) can normalise brightness in the image.
Use of high quality corrected lenses with solid lens construction. Don't save money in the wrong place!
However, this can lead to vignetting, especially when using the largest sensors, as pixels close to the edge are only exposed at an angle. This can be corrected by using double-sided telecentric lenses or by switching to a larger mount, e.g. from C-mount to F-mount.
Extreme vignetting is often caused by insufficient or inhomogeneous illumination and rarely by the optics. Size matters! Use bigger, better lighting!
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