Palm Print/Vein SDK

1. High Security (Core Advantage)

Living-body Uniqueness: Palm vein is a subcutaneous biometric feature that cannot be replicated by forgery such as photos, silicone molds or severed palms. Combined with palmprint surface features, dual verification greatly improves security, far higher than passwords, fingerprints (easily copied) and face recognition (easily tricked by photos/videos);

Contactless: No direct pressing on the capture device, reducing contact contamination and avoiding wear issues of fingerprint recognition;

Unalterable Features: Palmprint and palm vein features are stable for life, unchanged by age or minor epidermal injuries, and cannot be modified artificially.

2. Usability Adapted for Android Platform

Lightweight Optimization: Algorithm optimized for Android systems (Android 8.0+ mainstream versions), with low memory and computing power consumption on mobile phones/terminals and fast response (recognition time < 1 second);

Multi-device Compatibility: Supports Android phones, smart door locks, attendance machines, access control terminals and other hardware forms. Connectable to external capture modules via USB/Bluetooth, or compatible with Android devices equipped with built-in near-infrared cameras;

Easy Integration: Provides standard Android SDK (including API interfaces and usage examples), allowing developers to quickly integrate into apps and system-level applications, with offline recognition supported (no network required).

3. High Recognition Accuracy & Robustness

Fusion Algorithm Advantage: Single palmprint recognition error rate is about 0.1%, single palm vein about 0.01%. After fusion, False Rejection Rate (FRR) < 0.005% and False Acceptance Rate (FAR) < 0.0001%, with accuracy far exceeding single biometric recognition;

Environmental Adaptability: Palmprint + palm vein fusion complements each other — even with stains or minor scratches on the palm (affecting palmprint), palm vein can still recognize stably;

User-friendly Capture: Large recognition area (whole palm), no precise alignment needed, providing better user experience than fingerprint (which requires alignment with the sensor).

4. Privacy & Compliance

Local Storage: Feature data can be encrypted and stored locally on Android devices without cloud upload, complying with the Personal Information Protection Law and Data Security Law;

Irreversible Features: Collects feature values of palmprint/palm vein (not original images), which cannot be restored to real palm images, preventing privacy leakage;

Controllable Permissions: Follows Android system permission mechanism. Capture and storage of feature data only after user authorization for camera/storage permissions.

1. Security Shortcomings of Traditional Identity Authentication

Solves issues such as easy leakage and theft of passwords/verification codes, easy replication of fingerprints (e.g., fingerprint films), and face recognition being deceived by photos/3D models;

Fixes security loopholes including clocking in for others and identity fraud in access control, payment and other scenarios, especially suitable for high-security fields such as finance, government services and enterprise office.

2. Insufficient Reliability of Single-Modal Biometric Recognition

Solves the problem that pure palmprint recognition is easily affected by skin conditions (dryness, stains, aging), and pure palm vein recognition has high hardware requirements and poor adaptability;

Improves user experience by avoiding verification failure due to a single failed capture in single-modal recognition; fusion recognition supports fault tolerance and increases pass rate.

3. Adaptation and Implementation Issues of Biometric Recognition on Android

Resolves poor compatibility across different Android devices (brands, system versions, hardware configurations), and the standardized SDK reduces integration costs;

Supports identity authentication in offline scenarios (e.g., access control and industrial terminals without network), independent of cloud servers, thus improving availability.

4. Privacy and Compliance Issues in High-Security Scenarios

Eliminates leakage risks caused by cloud storage of biometric feature data; local encrypted storage complies with privacy regulations;

Ensures compliant use of biometric data for employee identity verification and visitor management in enterprises and institutions.

5. Recognition Adaptation in Special Scenarios

Enables normal biometric recognition for people with worn fingerprints (e.g., manual workers) and those with occluded faces (e.g., wearing masks);

Removes hygiene risks of contact-based recognition devices in public places (e.g., hospitals, subways) with safer contactless capture.