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MegaMatcher.

MegaMatcher is aimed at developers of large AFIS and multi-biometric systems, with high reliability and speed of biometric identification of large databases, supporting fingerprint, iris, face, voice, and palms on Microsoft Windows, Linux, macOS, iOS, and Android platforms.

Features of the MegaMatcher.

MegaMatcher is a software development kit that enables the creation of large-scale single or multi-biometric identification products.

MegaMatcher 13.0 Standard SDK - 2590 euros.

MegaMatcher 13.0 Extended SDK - 4990 euros.

The project cost is calculated upon request.

MegaMatcher capabilities.

Performance and platforms
Development platforms

MegaMatcher is designed for developers of large AFIS and multi-biometric systems. The technology ensures high reliability and speed of biometric identification even when using large databases.
Available as a software development kit that enables the development of large-scale fingerprint, iris, face, voice, or palm identification products for Microsoft Windows, Linux, macOS, iOS, and Android platforms.
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Fingerprinting and matching
Fingerprint pattern extraction and matching mechanism

Fully MINEX compliant.NIST has recognized the MegaMatcher fingerprint algorithm as MINEX compliant and suitable for use in identity verification (PIV) software applications.
The MegaMatcher fingerprint engine compares curled and flat fingerprints against each other.
MegaMatcher contains fingerprints and image quality determination, only the best-quality fingerprint template will be stored in the database.
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Face and juxtaposition
Face pattern extraction and matching mechanism

Tolerance to the position of the face provides a level of ease of registration. MegaMatcher allows you to rotate your head 360 degrees. The tilt of the head can be up to 15 degrees in each direction from the frontal position.
The angle of rotation of the head can be up to 45 degrees in each direction from the frontal position. For more information, see Specifications.
Reliable facial recognition ensures accurate registration from cameras, webcams, and various scanned documents. Faces can be registered from scanned pages of a passport or other types of documents.
MegaMatcher can estimate a person's age by analyzing the detected face.
Recognition of facial features. MegaMatcher can be configured to detect certain facial features such as a smile, open mouth, closed eyes, glasses, dark glasses, beard, and mustache.
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Voice patterns and correspondences
MegaMatcher voice pattern extraction and matching mechanism

Text-dependent mechanism voice matching determines whether a voice sample matches a pattern extracted from a given text. During registration, the person registering is asked for one or more phrases. Later, that person may be asked to speak a particular phrase from the same text for verification. This method protects against using this person's secretly recorded voice for authentication.
Two-factor authentication using a passphrase is performed when a person is asked to enter a unique phrase (for example, a password or the answer to a "secret question", that is, known only to the registered person) and speak a certain phrase from the text. The overall security of the system is increased because the authenticity of the voice and the entered password are verified.
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Iris pattern
Irises MegaMatcher pattern extraction and matching mechanism

Tested for reliability by NIST IREX. MegaMatcher's iris matching engine is based on VeriEye, which has been recognized by NIST as one of the most reliable iris recognition algorithms available.
Quick comparison. Iris matching speed is up to 200,000 comparisons per second on a single PC.
The iris is detected even in the presence of image obstructions, visual noise, and/or different light levels. Light glare, and clogging of the eyelids and eyelashes are eliminated.
Automatic interlacing detection and correction ensures maximum quality iris feature patterns from moving iris images.
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Technological awards

MegaMatcher technology has received numerous awards and certificates of conformity from international and scientific bodies.

Results of FVC-onGoing

The fingerprint extractor and matchbook were found to be the best and most accurate for the FV-STD-1.0 and FV-HARD-1.0 tests or less.

Evaluation of PFT II and PFT III

Our recent submissions to PFT II and the current PFT III average the most accurate algorithms across all experiments.

WSQ 3.1 FBI

In 2011, the FBI certified Neurotechnology's implementation of support for the WSQ image format.

Evaluation of SlapSeg III

Neurotechnology's fingerprint segmentation algorithm was rated by NIST as the most accurate.

FpVTE evaluation by NIST

NIST recognized Neurotechnology's fingerprint identification algorithm as one of the fastest and most accurate among the evaluation participants.

IREX estimates from NIST

In 2020, NIST rated Neurotechnology's iris recognition algorithm as the second most accurate among IREX 10 participants.

FRVT Ongoing

In 2018, Neurotechnology was among the 8 most accurate suppliers of face recognition algorithms.

FIVE (Face in Video Evaluation)

2018 - on average, the presented algorithm was among the 8 most accurate facial recognition algorithms from 16 providers.

MINEX estimates from NIST

MINEX III evaluation was successfully completed in 2015. MegaMatcher technology has been recognized by NIST as fully compatible with MINEX.

Productive system architecture

The MegaMatcher SDK is designed for large-scale AFIS / ABIS projects and includes specialized components and biometric engines for biometric data collection, pattern extraction, and matching.

Some of the components are designed to provide high performance for a large number of queries and/or large databases with millions of biometric templates, while others provide easy deployment to client sites at a reasonable price. In addition, some components are designed to build systems with lower performance requirements.

System architectures and components are used for specific projects

Client-side template generation and server-side matching
For AFIS, border control, various identification systems (passports, identity cards, voter registration).
Server-side template generation and matching
Recommended for online banking, government e-services and other mass systems where requests can be sent from any device.
Deduplication after collecting all user data
Recommended for ID systems that previously collected biometric data, such as voter or population registry cleanups
Create and select templates on one computer or device
Recommended for stand-alone deployments such as desktop or mobile, civilian or forensic identification systems.