Zum Hauptinhalt springen

Rule-based machine vision -
Classic industrial image processing

The rule-based machine vision is an industrial image processing technology that is based on defined parameters and test criteria based. It works reliably as long as the product and production conditions do not change and is particularly suitable for simple, recurring testing tasks.

In contrast to AI-based approaches, errors are not detected by learning from data, but by Predefined ruleswhich describe exactly which features of a product are considered correct or faulty. This makes the technology particularly straightforward and immediately usable.

Discover our data-centric AI solution

Strengths of
rule-based machine vision

  • Good precision for clearly defined tasks:
    If products and fault patterns are predictable, the system delivers reliable results.
  • Low system complexity:
    With stable requirements, the structure of the solution is comparatively simple and quick to implement.

Boundaries of
of the method

Manual adjustment in the event of changes:

Each new product variant or modification requires a manual adjustment of the rules.

Limited flexibility:

Difficult to define, variable or complex error patterns can only be captured to a limited extent with this approach.

High maintenance costs and low scalability:

With increasing product diversity, effort and costs increase significantly, which limits long-term adaptability.

These properties make rule-based machine vision particularly suitable for Simply structured, consistent test taskswhile for processes with high variability or complex surfaces AI-based approaches like the Data-centric AI as a deep learning solution for industrial image processing are more flexible and efficient in the long term.

Rule-based
Machine Vision
in Industry

Rule-based machine vision systems offer a Good, immediately available and easy to implement solution for standardized, stable production tasks. For varying products or complex error patterns, however, they quickly reach their limits. Companies should therefore Growth strategyand the Product and process complexity to choose the right approach for industrial image processing - be it classic machine vision for very simple applications or AI-based methods for flexible, data-driven quality controls.

Take advantage of the benefits of our Data-centric AI solution now!

Model-centric AI, anomaly detection with AI and machine vision systems can deliver excellent results in clearly defined, stable production environments - especially if error patterns are known and processes are largely constant.

In many modern production facilities, however, components, materials or process parameters change regularly. In such cases, classic systems quickly reach their limits, as they are dependent on fixed models or rules.

If you are looking for a solution that constantly adapts to new data, reliably detects complex error patterns and works stably despite varying conditions, we recommend the data-centric deep learning approach.

Find out here how data-centric AI can take your quality assurance to the next level.

Test data-centric AI now!