Code and models for paper "Robust Minutiae Extractor: Integrating Deep Networks and Fingerprint Domain Knowledge" at International Conference on Biometrics (ICB) 2018
A system for identifying latent fingerprints. Created at Michigan State University by Anil K. Jain, Kai Cao, Dinh-Luan Nguyen, and Cori Tymoszek.
Resources for NIST's Evaluation of Latent Friction Ridge Technology
A research project on a tool for annotating biometric data and a forensic expert’s workflow
Resources for NIST's Friction Ridge Image and Features Technology Evaluations
Complete educational AFIS (Automated Fingerprint Identification System) built in Python. Implements the full fingerprint recognition pipeline: acquisition, preprocessing (Gabor filters, skeletonization), minutiae extraction, template storage (SQLite), and matching (1:1 & 1:N). Perfect for learning biometrics and computer vision.
Pure-TypeScript port of SourceAFIS 3.18.1 fingerprint recognition (extractor + matcher), bit-exact vs the Java reference. Zero dependencies.
Open Source Biometric Voter Registration System
Desktop Python application to import AFIS reports, extract structured data and export analysis artifacts.
Desktop application for viewing, editing and comparing ANSI/NIST-ITL biometric files.
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