A remote identity verification pipeline that relies on check digits rather than guesswork when reading ID cards — with face matching and liveness built without using real personal data.
On an ID Card, the Text You Read Is Not the Thing to Trust
Most remote identity verification systems read the front of the card and trust what they read. We measured it: on real cards, front-side OCR reads only ~77% of fields exactly right. So we anchored trust somewhere else — the machine-readable zone (MRZ) on the back of the card.
The MRZ carries its own proof through ICAO 9303 check digits. If a value fails its check digit, it is wrong — there is no room for guessing. Front-side reading is supporting evidence only: the Turkish national ID number is validated with its own algorithm, single-character OCR errors are recovered through that rule, and dates and names pass plausibility checks.
The card's owner must be proven too. The card photo and a live selfie are matched through face embeddings, with the threshold set by a calibration tool that measures false-accept and false-reject rates. The user is asked for randomized head movements, and passive anti-spoofing runs against a photo held up to the camera. Development ran on synthetic cards we generated, not on real ID cards — so there is no personal-data burden from the start.
How It Works
- MRZ-canonical trust model: ICAO 9303 check digits
- Front OCR as support only; error recovery via the national ID algorithm
- Card detection, perspective correction, auto-rotation by OCR vote
- Face matching with a calibrated threshold (ArcFace)
- Randomized head-pose liveness, passive anti-spoofing
- Synthetic data and a 9-scenario accuracy harness
What We Learned
We dropped a field-detection model trained on synthetic cards because it missed fields on real ones, and stripped the pipeline of heavy deep-learning dependencies. Measuring accuracy on real cards rather than demo cards is what made that call.
Where We Use It
In UNITICID, our own remote identity verification pipeline. The same face-matching foundation also lets Hardiye recognise returning customers without storing their photos.
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