Illumination is one of the most critical components of a machine vision system. The selection of
the appropriate lighting component for a specific application is very important to ensure that
a machine vision system performs its tasks consistently and reliably.
The main reason is that improper illumination results in loss of information which, in most cases,
cannot be recovered via software. This is why the selection of quality lighting components is of
primary importance: there is no software algorithm capable of revealing features that are not
correctly illuminated.
To make the most appropriate choice, one must consider many different parameters, including:
- Lighting geometry
- Light source type
- Wavelength
- Surface property of the material to be inspected or measured (e.g. color, reflectivity)
- Item shape
- Item speed (inline or offline application)
- Mechanical constraints
- Environment considerations
- Cost
Since many parameters must be considered, the choice can be difficult and sometimes the wisest
advice is to perform feasibility studies with different light types to reveal the features of interest.
On the other hand, there are a number of simple rules and good practices that can help select the
proper lights and improve the image quality.
For every application, the main objectives are the following:
- Maximizing the contrast of the features that must be inspected or measured
- Minimizing the contrast of the features of no interest
- Getting rid of unwanted variations caused by:
- Ambient light
- Differences between items that are non-relevant to the inspection task
