Herdmark Biometric identity register
API up Embedder DINOv2 Gallery 88
Step 3 of 8 · The control that is worth money

The duplicate block

One animal, presented twice, as two different animals. That is how a herd of 200 gets financed as a herd of 300, and how the same cow is insured by two insurers who each believe they hold the only policy. Ear tags cannot close this, because a tag is a thing you can buy. This is the fraud vector the registry exists to close.

Real muzzle photographs · no accuracy claim is being made
The images on this screen are real cattle muzzle photographs from a public research dataset — US feedlot cattle, photographed in a single session. They are not South African breeds and none is a Cape buffalo. No score shown anywhere in this console is evidence of real-world accuracy.
Imagery Xiong, Yijie; Li, Guoming; Erickson, Galen (2022). Beef Cattle Muzzle/Noseprint database for individual identification [Dataset]. Zenodo. https://doi.org/10.5281/zenodo.6324361. Licensed under CC BY 4.0https://creativecommons.org/licenses/by/4.0/.
Read the full disclosure

The gallery holds 12 animals and 168 frames. Twelve animals is a demonstration, not a register. Accuracy on twelve animals says nothing about accuracy on a hundred thousand: the chance of a stranger resembling someone already enrolled grows with the size of the register, and this gallery is far too small to show where that starts to bite.

The imagery is single-session. Every frame of an animal was taken on one occasion. That includes the "second capture" used on the duplicate-check screen — it is a different part of the same session, not a return visit. So this console can show that the duplicate block fires; it cannot show that a muzzle still matches weeks or months later. Whether a muzzle pattern is durable over time is the question that decides whether this product works, and no public dataset we are permitted to use commercially can answer it. It needs a longitudinal capture: the same South African animals photographed twice, weeks apart.

The population is wrong for this market. US Midwest feedyard beef yearlings; Angus, Angus x Hereford, Continental x British cross. No Bonsmara, no Nguni, no Afrikaner, no Cape buffalo. A Cape buffalo muzzle has not been put through this pipeline at all.

What the pipeline underneath does show is real, and it is the part worth watching: capture, quality gate, DINOv2 embedding, vector search, thresholding and the hash-chained audit record all run exactly as they would in production, on real photographs, with the thresholds read from the database at request time.

Where this console cannot determine something it says unknown. It never reports "real" on the strength of a guess.

Re-present an animal that is already registered

Pick a capture of an animal the registry has already enrolled — different frames, never the same file resubmitted — and attempt to enroll it as new.

Refused with HTTP 409 and no animal created whenever the 1:N score reaches the block threshold in force.