5 things that are often forgotten at the start of a vision project

Lighting: A machine vision system is highly dependent on the ambient lighting in the installation. Factors such as sunlight, shadows from moving objects, or artificial light sources can affect image quality. Poor or fluctuating lighting leads to varying contrasts and unreliable detections, especially with shiny or transparent objects.

How to solve this?

• Use diffuse or polarized lighting to reduce reflections.

• Test different lighting techniques such as backlight, coaxial, or dome lighting.

• Simulate lighting conditions in advance in a test environment such as the Center of Excellence at Heliovision.
  

2. Calibration and Maintenance A camera captures raw pixel information, but without proper calibration, measurements can be distorted. Factors such as lens distortion, perspective deviations, and scale differences play a major role. External influences such as temperature changes and vibrations can disrupt calibration, leading to measurement errors.

How to prevent this?

• Perform regular recalibration, especially for precision applications such as robotic guidance or dimensional measurements.

• Use automatic calibration methods or reference objects to detect deviations in time.

• Ensure a stable mounting and regularly check for wear.
  

3. Cycle Time The speed of image processing is often underestimated, especially in 3D imaging, where processing times are longer than in 2D. Factors such as image acquisition, filtering, analysis, and data exchange contribute to the total cycle time. Delays can arise from slow image processing, insufficient hardware performance, or network latency. That is why our vision systems are always equipped with an industrial PC to minimize cycle time, especially with complex software and AI algorithms.

How to optimize cycle time?

• Use an industrial PC to minimize cycle time.

• Test in advance with expected production speeds to avoid bottlenecks.

• Adjust the resolution to the available computing power to reduce delays.
  

4. Effect of Vibrations on Image Quality Vibrations in a machine vision system can cause subtle but critical distortions in the image. Even small mechanical vibrations from motors, conveyor belts, or other machines can lead to blurry or distorted images. This effect is problematic with long exposure times or high magnification factors, where small movements are magnified. Rolling shutter cameras are particularly sensitive because different parts of the image are captured at different moments.

How to prevent this issue?

• Use vibration dampers and rigid mounting frames.

• Work with short exposure times or a global shutter camera.

• Ensure a stable mechanical setup to avoid motion artifacts and guarantee consistent image quality.
  

5. A Camera Cannot Measure Absolutely A camera only captures 2D pixel information, which does not directly provide a reliable measurement of distances or dimensions. Lens distortion, perspective, and depth differences can affect measurement results.

How to ensure accurate measurements?

• Use calibration with a reference object or an advanced optical model.

• For 3D measurements, stereo vision or laser triangulation is necessary.

• Consider angular deviations and lighting differences in measurements.

When corrections and calibrations are properly executed, cameras can actually be a very efficient and fast way of measuring compared to traditional measurement benches and probes.