afis

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.

ANSI/NIST-ITL biometric file viewer, editor, validator and converter for Windows, with NFIQ2 fingerprint quality analysis.

Open Source Biometric Voter Registration System

Open-source cross-platform viewer for EFT / ANSI-NIST-ITL biometric files — view fingerprint (WSQ), demographic, and transaction records. Windows · macOS · Linux.

Read, write and validate ANSI/NIST-ITL biometric files (NIST, EBTS, INT-I) in Rust — byte for byte compatible with nistitl, 3–4× faster