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Documentation Index

Fetch the complete documentation index at: https://mintlify.com/usnistgov/NFIQ2/llms.txt

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Fingerprint Quality Assessment for Biometric Systems

NFIQ 2 is the NIST Fingerprint Image Quality assessment library, implementing the ISO/IEC 29794-4 international standard for unified quality scoring of 500 PPI fingerprint images.

Get StartedAPI Reference

Quick Start

Get up and running with NFIQ 2 in minutes

1

Download pre-built binaries

Download the latest version from GitHub Releases for your platform (Windows, macOS, or Linux). Pre-built libraries and CLI tools are available.
2

Include headers in your project

Add the NFIQ 2 headers to your C++ project:
#include <nfiq2.hpp>
Headers are installed in /usr/local/nfiq2/include on macOS and Linux, or C:\Program Files\NFIQ 2\include on Windows.
3

Load the random forest model

Initialize the algorithm with the included model parameters:
NFIQ2::ModelInfo modelInfo("nist_plain_tir-ink.txt");
NFIQ2::Algorithm model(modelInfo);
4

Compute quality scores

Process your fingerprint images to get unified quality scores:
NFIQ2::FingerprintImageData rawImage(
    pixels, size, width, height, fingerPosition, 500
);
unsigned int qualityScore = model.computeUnifiedQualityScore(rawImage);
Quality scores range from 0-100, where higher values indicate better quality images for biometric matching.

Key Features

Standards-compliant quality assessment for operational fingerprint systems

ISO/IEC 29794-4 Compliant

Officially recognized reference implementation of the international biometric quality standard.

Unified Quality Scores

High-resolution quality scores on a 0-100 scale for precise quality assessment.

Native Quality Measures

Extract detailed quality metrics including FDA, LCS, OCL histogram, and minutiae-based measures.

Actionable Feedback

Get specific feedback to guide image capture and improve fingerprint quality.

Cross-Platform Support

Works on Windows, macOS, Linux, Android, and iOS platforms.

CLI and Library

Use as a C++ library in your application or via the standalone command-line tool.

Explore the Documentation

Learn how to integrate NFIQ 2 into your biometric systems

Core Concepts

Understand quality scores, native measures, actionable feedback, and the random forest model.

Learn more

Developer Guides

Step-by-step guides for computing scores, extracting quality measures, and embedding models.

View guides

API Reference

Complete C++ API documentation for all classes, methods, and quality modules.

Browse API

CLI Tool

Learn to use the command-line interface for batch processing and testing.

CLI docs

Ready to Get Started?

Download NFIQ 2 from GitHub and start assessing fingerprint quality in your biometric applications today.

Quick Start GuideDownload from GitHub