Depth of Field in Machine Vision
Machine-vision depth of field is the object range that preserves enough task contrast, not simply the range that looks acceptably sharp. Aperture, magnification, sensor sampling, illumination, motion, lens aberration, and the allowed decision threshold must be evaluated together.
Why this decision matters
This choice affects more than nominal optical performance. It changes package volume, tolerance sensitivity, supplier options, alignment effort, calibration, test equipment, production yield, and the evidence required before release. The correct answer therefore comes from the complete operating condition and acceptance method, not from a single catalog value.
Key engineering decisions
- Define acceptable contrast at the task feature.
- Balance aperture against diffraction and signal.
- Include object tilt and mechanical variation.
These decisions should be captured in a requirement or trade study before the team commits long-lead components. Where requirements conflict, rank the product priorities explicitly so optimization does not hide a business decision.
Specification checklist
- Near and far object planes
- Feature frequency
- Aperture range
- Exposure and illumination
- Focus adjustment method
Every value should state the condition where it applies and how it will be measured. A specification without a defined test condition is not yet an acceptance requirement.
Common failure mode
Stopping down improves geometric depth but creates diffraction, low signal, or long exposure that defeats the task.
The practical remedy is to compare the nominal model, tolerance prediction, mechanical interfaces, and measured configuration together. Treating the symptom as an isolated lens or component problem often produces another build with the same system-level limitation.
Verification approach
Test representative features at depth extremes, field points, motion states, and production illumination.
Record the hardware revision, source or scene, wavelength, aperture, field point, focus or alignment state, environmental condition, processing, and measurement uncertainty. This makes the result useful for design iteration and supplier transfer rather than only for a one-time demonstration.
What to send PAO
Send depth range, feature size, field, sensor, working distance, motion, lighting, and pass/fail images.
PAO applies this framework through robotics and machine-vision optics, from requirements and architecture through detailed design, prototype evidence, and manufacturing transfer.