Glossary · Machine vision
Optical character verification (OCV)
Also known as: OCV, Print verification
German: Optische Zeichenprüfung (OCV)
In machine vision, optical character verification (OCV) checks that a known, expected text string is present and correctly printed, usually by comparing each character with a trained reference and grading its quality.
- Machine vision
In one sentence
Optical character verification (OCV) checks that expected text is present and printed correctly, grading each character against references.
Example
OCV confirms that the lot number on each blister foil matches the lot number of the running order and that no character is broken.
How it applies
- Engineering: OCV is used where the correct content is known in advance, such as regulated labeling of lot numbers and expiry dates. It detects both wrong content and poor print quality.
- Operation: The expected string comes from the order data; the interface that transfers it must be reliable, because a wrong expected value makes the check meaningless.
- Documentation: The documentation team should document the data flow of expected strings, quality thresholds and the procedure for rejected packs, and, in regulated industries, how the check is validated.
OCV vs. OCR
Optical character recognition (OCR) reads text it does not know; OCV confirms text it expects. OCV answers pass or fail; OCR delivers the text.