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Vision AI

OCR for Batch Numbers, Expiry Dates and Product Labels

Plan code reading, expected-value checks and traceability for printed production information.

Author: Baztech Engineering2 min read

Reading characters and deciding whether they are correct are separate inspection tasks. Industrial OCR needs both a usable image and a trusted rule for the expected label content.

Specify the fields and formats

List batch codes, dates, serials and variable text with allowed formats. Define date order explicitly to avoid day-month ambiguity. Decide whether the system reads unknown text or verifies a known expected value. Obtain that expected value from an approved production record, not from the same image being checked.

Control the printed-image conditions

Test font size, contrast, curved surfaces, reflective film and print-position variation. Check the smallest characters at production speed. A blurred or partially hidden code should be marked unreadable rather than guessed. Consider a dedicated view or illumination arrangement when the general inspection camera cannot resolve the text.

Validate the entire field

Evaluate exact-field matches, not only average character accuracy. Confusions such as O and 0 can invalidate a whole serial number. Use permitted format checks but do not automatically repair ambiguous text without a documented rule. Store read, expected and decision values separately so later investigations can reconstruct the result.

Test changeovers and exception handling

Include missing print, wrong batch, expired recipe, smeared ink and new packaging. Verify the expected code changes with the production order. Define manual review and reject handling for unreadable results. Traceability retention should follow the project’s actual needs rather than storing every image indefinitely.

FAQ

Is OCR the same as barcode reading?

No. OCR interprets printed characters; barcode decoding interprets a defined symbol format. They can complement each other.

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