Fingerprint Identification

ROC fingerprint recognition software ingests a fingerprint image - latent, tenprint, or palmprint - applies proprietary deep-learning feature extraction to generate a compact biometric template, then performs 1:1 verification or 1:N identification against databases of any size.

ROC uses the same core neural network techniques that power its #1-ranked face recognition, giving fingerprint matching unprecedented speed at forensic-grade accuracy. Template sizes are the smallest in the industry - reducing storage overhead and enabling large-scale deployments without infrastructure bottlenecks.

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Five independent NIST rankings confirm ROC's fingerprint performance:

• #1 globally in combined speed and accuracy - NIST PFT III
• #1 most sensor-interoperable algorithm on the planet
• #1 cross-sensor accuracy on IARPA Nail-to-Nail evaluation sets
• 10,000x faster search speed than industry standard
• Smallest template size - 160x smaller than the nearest competitor

These are independently verified results from the National Institute of Standards and Technology - not self-reported metrics.

Source: NIST PFT — Deployed by: FBI, U.S. Marshals, DoD

Latent fingerprints are partial friction-ridge impressions left unintentionally at crime scenes - often incomplete, degraded, and challenging to analyze. ROC's latent matcher - NIST ELFT-ranked latent matcher - 42-minute average search time.

Faster matching means fewer cold-case backlogs, faster investigative leads, and - in time-sensitive cases - lives saved. ROC also supports contactless hyperspectral capture from up to 5 meters for no-touch field collection without chemicals.

Source: NIST ELFT, February 2024 — More: roc.ai/abis

ROC fingerprint recognition accuracy is validated by three independent NIST evaluations:

• NIST PFT III - #1 in Nail-to-Nail benchmarks, lowest mean error rate across all sensor categories
• NIST ELFT - #1 rank-1 accuracy on the largest dataset with fastest search speeds (Feb 2024)
• IARPA cross-sensor - #1 most accurate across all sensor types

For forensic applications, this means fewer false matches, fewer missed identifications, and biometric evidence that withstands court scrutiny. All performance data is independently verified - not self-reported.

Source: NIST ELFT

Legacy AFIS systems from Idemia, NEC, and Cogent were built in the 1990s-2000s on proprietary hardware stacks that are expensive to maintain and slow to modernize. ROC ABIS replaces them with a cloud-native, open architecture:

• 10,000x faster search speeds vs. industry standard
• 160x smaller templates, dramatically reducing storage costs
• Cloud, on-premise, or edge - one architecture for all three
• Open and interoperable - standard biometric data formats for seamless migration
• One of the lowest total costs of ownership in the industry

Most agencies see a positive ROI within the first year through reduced infrastructure and processing overhead.

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ROC Fingerprint SDK supports all three forensic fingerprint types in a unified workflow - no separate system per type:

• Latent - partial friction-ridge impressions from crime scenes, often incomplete or degraded
• Tenprint - standardized 10-finger rolled and flat captures for booking and background checks
• Palmprint - full palm captures that expand identification surface area in ABIS deployments

All three types feed into a single search query - submit latent evidence and search simultaneously across latent, tenprint, and palmprint databases in one API call. FISWG-compliant metadata is generated automatically for forensic chain-of-custody.

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ROC Fingerprint SDK runs on every major platform with no cross-compilation surprises:

• Operating systems: Windows, macOS, Linux (x86-64 and ARM), iOS, Android
• Languages: C++, Java, Python, C#, Go, Node.js, Rust

A free developer SDK license is available with same-day access - no procurement cycle required. Evaluation includes full documentation, sample code for all supported languages, CLI for batch processing, and direct access to senior engineering support.

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Yes. ROC supports contactless fingerprint capture - including hyperspectral imaging from up to 5 meters - with no chemicals, no physical contact, and no processing delays.

Key capabilities:

• Works with standard optical and hyperspectral capture devices
• Integrates directly with ROC ABIS for immediate 1:N database search
• Results available in seconds
• Compatible with edge-deployed hardware for remote field operations

Critical for patrol operations, border checkpoints, and any scenario requiring rapid non-cooperative identification without compromising officer safety.

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ROC provides dedicated senior engineering support - direct access to the developers who write the code, not a first-line helpdesk. Support covers:

• Integration and API guidance
• Performance optimization for your specific deployment scale
• Troubleshooting across all supported platforms and modalities

Pricing is flexible: per-device, per-stream, or per-transaction - structured to match your deployment model. A free 30-day developer license includes full support access from day one.

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ROC Fingerprint Recognition SDK is designed to scale seamlessly across a wide range of deployments, from small-scale applications to enterprise-level systems. Our SDK is optimized to handle high volumes of fingerprint data efficiently, enabling rapid identification and authentication even in scenarios with a large user base.