Certified Dental Biometric Verification Under Partial Overlap

Abstract

Dental identification is usually evaluated as closed-set retrieval: given a dental scan, rank the enrolled gallery and report whether the correct subject appears first. This framing hides two operational requirements. First, forensic and clinical deployments need an accept/abstain decision with a controlled false-match rate (FMR), not only a Rank-1 score. Second, practical queries are often partial: field-of-view limits, trauma, extractions, and missing teeth break the rigid alignment assumption used by most 3D dental matching pipelines. We present ToothPrint, a dental biometric verification pipeline for 3D intraoral scans and 2D radiographs that combines rigid surface verification, learned partial-overlap correspondence, and split-conformal calibration. On 200 public 3D dental arches, rigid surface verification achieves Rank-1 0.995 and EER 0.005 under full coverage. Under realistic whole-tooth dropout, however, rigid GICP falls to Rank-1 0.23 at 50% tooth retention. A learned point-correspondence verifier lifts this regime to Rank-1 0.867 (AUC 0.984), while a crop-hardened embedding baseline reaches 0.635. The same score family supports a conformal open-set decision: full-coverage FNIR at FMR=1% is 0.00, while heavy tooth loss is correctly exposed as an abstention regime. We report DET curves, hard-negative calibration, an untrained-correspondence control, a cross-dataset transfer test on Teeth3DS+, and auxiliary 2D radiograph and restoration-pattern results. The central limitation is explicit: because available public 3D dental scans are mostly single-session, identity queries are synthetic reacquisitions. The method is therefore evidence for a research direction, not a clinical claim.