A unified framework combining nonparametric 3D unwrapping, point-cloud fusion, ellipse-based pose normalization, and pose-aware registration to enable ridge-level compatibility between 3D and both contactless and contact-based 2D fingerprints.
Towards contactless, low-cost and accurate 3d fingerprint identification
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
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cs.CV 2years
2026 2verdicts
UNVERDICTED 2representative citing papers
B-spline curve fitting unwraps 3D fingerprint point clouds into 2D grayscale images, achieving EERs of 0.2072%, 0.26%, and 0.22% and outperforming prior 3D methods in cross-session tests.
citing papers explorer
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Cross-Modal Registration Between 3D and 2D Fingerprints via Pose-Aware Unwrapping and Point-Cloud Fusion
A unified framework combining nonparametric 3D unwrapping, point-cloud fusion, ellipse-based pose normalization, and pose-aware registration to enable ridge-level compatibility between 3D and both contactless and contact-based 2D fingerprints.
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A B-Spline Function Based 3D Point Cloud Unwrapping Scheme for 3D Fingerprint Recognition and Identification
B-spline curve fitting unwraps 3D fingerprint point clouds into 2D grayscale images, achieving EERs of 0.2072%, 0.26%, and 0.22% and outperforming prior 3D methods in cross-session tests.