Knowledge · Cameras
Camera selection starts with geometry and task, not megapixels. Use sensor type, optics, lighting, FOV and triggering to shortlist hardware with confidence.
Start here
This hub covers full camera selection after geometry is set. Start with the fork below: decide whether your scene is a continuous web or belt, or a discrete field of view per cycle. That choice drives sensor geometry, encoder needs and lens strategy.
The selection fork: continuous motion vs discrete FOV, encoder sync and when each geometry wins on the factory floor.
Sensor types
What each family is — definitional teasers. Geometry choice starts at the line scan vs area scan page; return here for optics, lighting and triggering after you know the family.
What an area scan camera is: full-frame 2D capture for discrete field-of-view inspection in one exposure.
What a line scan camera is: builds a 2D image line by line as continuous material moves past the sensor.
What a smart camera is: image capture and processing in one device for standalone inspection stations.
What a 3D camera is: depth and shape capture for metrology, volume and robot vision including bin picking paths.
Optics and illumination
Resolution on the datasheet means nothing if the lens does not deliver the FOV and contrast your algorithm needs. Pair lens, lighting and triggering with the camera geometry you chose above.
Beyond hardware
Sensor geometry is step one. Step two is how you process images: smart camera vs PC, classical rules vs AI, 2D vs 3D for robot vision. The vision architecture guide links those decisions without repeating sensor basics.
Go to vision architectureBrowse our camera catalog or share your FOV, interface and cycle-time targets. We help you match geometry to available models.