Rule-based image processing or AI – what is the difference?
Many projects start with the question: ‘Do we already need AI – or is classic image processing sufficient?’ The short answer: both have their place.
A simplified overview:
Rule-based systems work with clearly defined inspection rules (edges, contrasts, geometries). They are transparent, stable and very easy to validate.
AI/deep learning methods are suitable when defect images are highly variable or difficult to define in rules. They ‘learn’ from examples and can recognise complex patterns.
Hybrid approaches combine both – e.g. classic geometry inspection plus AI-based surface analysis.
The decisive factor is not the ‘hype factor’, but rather: Which method delivers robust, traceable results in your process – even in an audit?