Android library to simplify Biometric authentication implementation.

Face recognition SDK Android with 3D passive liveness detection (Face Detection, Face Landmarks, Face Recognition, Face Liveness, Face Pose, Face Expression, Face attributes)

EDCC: An efficient and accurate algorithm for palmprint recognition.

This is an Android project allowing you to use the advanced biometric authorization features.

Easy access to native biometric auth APIs on iOS and Android

Browser-only utils for locally managing WebAuthn (passkey) API

Use fingerprint readers with a Linux desktop environment

Liveness detection SDK Linux - iBeta level 2 compliant 3D passive liveness detection engine which can detect printed photos, video replay, 3D masks, and deepfake threats

Two-stream CNN for gender classification and biometric identification using a dataset of 11K hand images.

Face Recognition SDK Javascript using ONNX Runtime Web and OpenCV.js (Face Detection, Face Landmarks, Face Liveness, Face Pose, Face Expression, Eye Closeness, Age, Gender and Face Recognition)

A minimalistic to do list app that performs CRUD operations. Made with .Net MAUI & SQLite. This app features optional biometric authentication, a dashboard with charts, camera & image gallery usage, ListView with bulk actions as well as dark & light themes.

Face recognition SDK & Face liveness detection SDK (Face Detection, Face Landmarks, Face Recognition, Face Liveness, Face Pose, Face Expression, Face attributes)

Apple bio metric authentication for touchID and faceID

The world's 1st free and open source palm recognition SDK for Windows and Linux (Palm detection, ROI extraction, Template extraction, Template mathcing)

Voice biometric authentication PAM module for Linux

Liveness detection SDK Android - iBeta level 2 compliant 3D passive liveness detection engine which can detect printed photos, video replay, 3D masks, and deepfake threats

Keycloak Workshop for Step Up with MFA Biometrics Authentication (Passkeys) and Passwordless experience with Passkeys

A robust algorithm for extracting ROI from palm image taken by mobile phone.

This is a collection of 10 000 unique digital fingerprints created based on the algorithm for generating basic rings using a noise texture. Like human fingerprints, you can now use them for the Web3 and Metaverse era as digital biometric information on The Open Network.