Eye iris Recognition

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Eye iris Recognition

facial recognition
Large-scale AFIS and Multi-biometric Identification

The iris of every man’s eye is as unique as his fingerprints. Each of our eyes has its own completely different iris with absolutely unique formations, which if no injury occurs, remain unchanged throughout our life. The diversity and complexity of these formations combined with their random distribution to the entire human population make iris usable in the development of biometric systems.

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Description

Operating principle

The identification procedure is done in two stages:

» It is initially necessary to digitally capture the iris of the eye from a distance with the use of a detector or a camera in the near infrared spectral region, where the formations of even the seemingly darker and amorphous Irises.
» Then the identification is achieved by the use of a composite algorithm (mathematical equation), which compares specific features of the digitized iris with the corresponding special traits of the irises, whose depictions They are kept in a database.

Applications
» Access Control in physical areas
» Security of software Use-user identification
» etc.

VeriEye SDK is based on VeriEye iris recognition technology and is intended for biometric systems developers and integrators. The SDK allows rapid development of biometric applications using functionality from the VeriEye algorithm that ensures relable fast iris identification. VeriEye can be easily integrated into the customer’s security system. The integrator has complete control over SDK data input and output.

VeriEye SDK includes the Device Manager library for working with the supported iris cameras. Integrators can also write plug-ins to support their iris cameras or other devices using the plug-in framework provided with the Device Manager.

VeriEye is available as the following SDKs:

  • VeriEye 13.0 Standard SDK is designed for PC-based, embedded or mobile biometric application development. It includes Iris Matcher and Extractor component licenses, programming samples and tutorials, iris scanner support modules and software documentation. The SDK allows the development of biometric applications for Microsoft Windows, Linux, macOS, iOS or Android operating systems.
  • VeriEye 13.0 Extended SDK is designed for biometric client-server application development. It includes all features and components of the Standard SDK. Additionally, the SDK contains Iris Client component licenses for PCs and mobile / embedded devices, sample client applications, tutorials and a ready-to-use matching server component.

There are specific requirements for each platform which will run VeriEye-based applications.

Microsoft Windows platform requirements

  • Microsoft Windows 7 / 8 / 10 / 11.
  • PC or laptop with x86-64 (64-bit) compatible processors.
    • 2 GHz or better processor is recommended.
    • AVX2 support is highly recommended. Processors that do not support AVX2 will still run the VeriEye algorithms, but in a mode, which will not provide the specified performance. Most modern processors support this instruction set, but please check if a particular processor model supports it.
    • The CPU plugin supports inference on Intel Xeon with Intel AVX2 and AVX-512, Intel Core processors with Intel AVX2, Intel Atom Processors with Intel SSE.
  • 2 GB of free RAM is recommended for general usage scenarios. It is possible to reduce RAM usage for particular scenarios. Also, additional RAM may be required for applications that perform 1-to-many identification, as all biometric templates need to be stored in RAM for matching.
  • Iris scanner:
    • VeriEye SDK includes support modules for several iris scanners under Microsoft Windows platform.
    • Iris images in BMP, JPG, PNG or WebP formats can be processed thus almost any third-party iris capturing hardware can be used with the VeriEye technology if it generates images in the mentioned formats.
    • Integrators may also write plug-ins to support their iris cameras using the plug-in framework provided with the Device Manager from the VeriEye SDK. The integrators should note, that the most accurate iris recognition is achievable only when iris images are captured with near-infrared cameras and appropriate illumination. However, it is still possible to recognize irises with reasonable accuracy, when the irises are captured with regular cameras, using proper illumination and focus, and choosing proper environment.
  • Database engine or connection with it. VeriEye templates can be saved into any DB (including files) supporting binary data saving. VeriEye Extended SDK contains the following support modules for Matching Server on Microsoft Windows platform:
    • Microsoft SQL Server;
    • MySQL;
    • Oracle;
    • PostgreSQL;
    • SQLite.
  • Network/LAN connection (TCP/IP) for client/server applications. Also, network connection is required for using Matching server component (included in VeriEye Extended SDK). VeriEye SDK does not provide communication encryption with the Matching server, therefore, integrators should secure the communication by themselves.
  • Microsoft .NET framework 4.5 or newer (for .NET components usage).
  • One of following development environments for application development:
    • Microsoft Visual Studio 2012 or newer (for application development under C/C++, C#, Visual Basic .Net)
    • Java SE JDK 8 or newer
    • Python 3.x

Android platform requirements

  • A smartphone or tablet that is running Android 5.0 (API level 21) OS or newer.
    • If you have a custom Android-based device or development board, contact us to find out if it is supported.
  • ARM-based 1.5 GHz processor recommended for iris processing in the specified time. Slower processors may be also used, but the iris processing will take longer time.
  • At least 1 GB of free RAM should be available for the application. Additional RAM is required for applications that perform 1-to-many identification, as all biometric templates need to be stored in RAM for matching.
  • Iris scanner:
    • VeriEye SDK includes support modules for several iris scanners under Android platform.
    • Iris images in BMP, JPG, PNG or WebP formats can be processed thus almost any third-party iris capturing hardware can be used with the VeriEye technology if it generates images in the mentioned formats.
    • Integrators may also write plug-ins to support their iris cameras using the plug-in framework provided with the Device Manager from the VeriEye SDK. The integrators should note, that the most accurate iris recognition is achievable only when iris images are captured with near-infrared cameras and appropriate illumination. However, it is still possible to recognize irises with reasonable accuracy, when the irises are captured with cameras, which are built in smartphones or tablets, using proper illumination and focus, and choosing proper environment.
  • Network/LAN connection (TCP/IP) for client/server applications. Also, network connection is required for using Matching server component (included in VeriEye Extended SDK). VeriEye SDK does not provide communication encryption with the Matching server, therefore, integrators should secure the communication by themselves.
  • PC-side development environment requirements:
    • Java SE JDK 8 (or higher)
    • AndroidStudio 4.0 IDE
    • AndroidSDK 21+ API level
    • Gradle 6.8.2 build automation system or newer
    • Android Gradle Plugin 4.1.2
    • Internet connection for activating VeriEye component licenses

iOS platform requirements

  • One of the following devices, running iOS 11.0 or newer:
    • iPhone 5S or newer iPhone.
    • iPad Air or newer iPad models.
  • At least 1 GB of free RAM should be available for the application. Additional RAM is required for applications that perform 1-to-many identification, as all biometric templates need to be stored in RAM for matching.
  • Iris scanner:
    • At the moment iris scanner support on iOS platform should be implemented by integrators. The integrators should note, that the most accurate iris recognition is achievable only when iris images are captured with near-infrared cameras and appropriate illumination. However, it is still possible to recognize irises with reasonable accuracy, when the irises are captured with cameras, which are built in smartphones or tablets, using proper illumination and focus, and choosing proper environment.
    • Iris images in BMP, JPG, PNG or WebP formats can be processed thus almost any third-party iris capturing hardware can be used with the VeriEye technology if it generates images in the mentioned formats.
  • Network/LAN connection (TCP/IP) for client/server applications. Also, network connection is required for using Matching server component (included in VeriEye Extended SDK). VeriEye SDK does not provide communication encryption with the Matching server, therefore, integrators should secure the communication by themselves.
  • Development environment requirements:
    • a Mac running macOS 10.13 or newer.
    • Xcode 9.3 or newer.

macOS platform requirements

  • A Mac running macOS 10.13 or newer.
    • 2 GHz or better processor is recommended.
    • x86-64 (Intel) and ARM (Apple M1 family) processor architectures supported.
  • 2 GB of free RAM is recommended for general usage scenarios. It is possible to reduce RAM usage for particular scenarios. Also, additional RAM may be required for applications that perform 1-to-many identification, as all biometric templates need to be stored in RAM for matching.
  • Iris scanner:
    • At the moment iris scanner support on macOS platform should be implemented by integrators. The integrators should note, that the most accurate iris recognition is achievable only when iris images are captured with near-infrared cameras and appropriate illumination. However, it is still possible to recognize irises with reasonable accuracy, when the irises are captured with regular cameras, using proper illumination and focus, and choosing proper environment.
    • Iris images in BMP, JPG, PNG or WebP formats can be processed thus almost any third-party iris capturing hardware can be used with the VeriEye technology if it generates images in the mentioned formats.
  • Database engine or connection with it. VeriEye templates can be saved into any DB (including files) supporting binary data saving. VeriEye Extended SDK contains SQLite support modules for Matching Server on macOS platform.
  • Network/LAN connection (TCP/IP) for client/server applications. Also, network connection is required for using Matching server component (included in VeriEye Extended SDK). VeriEye SDK does not provide communication encryption with the Matching server, therefore, integrators should secure the communication by themselves.
  • Specific requirements for application development:
    • XCode 9.3 or newer
    • GNU Make 3.81 or newer (to build samples and tutorials development)
    • Java SE JDK 8 or newer

Linux x86-64 platform requirements

  • Linux 4.9 kernel or newer is required.
  • PC or laptop with x86-64 (64-bit) compatible processors.
    • 2 GHz or better processor is recommended.
    • AVX2 support is highly recommended. Processors that do not support AVX2 will still run the VeriEye algorithms, but in a mode, which will not provide the specified performance. Most modern processors support this instruction set, but please check if a particular processor model supports it.
    • The CPU plugin supports inference on Intel Xeon with Intel AVX2 and AVX-512, Intel Core processors with Intel AVX2, Intel Atom Processors with Intel SSE.
  • 2 GB of free RAM is recommended for general usage scenarios. It is possible to reduce RAM usage for particular scenarios. Also, additional RAM may be required for applications that perform 1-to-many identification, as all biometric templates need to be stored in RAM for matching.
  • Iris scanner:
    • VeriEye SDK includes support modules for several iris scanners under Linux x86-64 platform.
    • Iris images in BMP, JPG, PNG or WebP formats can be processed thus almost any third-party iris capturing hardware can be used with the VeriEye technology if it generates images in the mentioned formats.
    • Integrators may also write plug-ins to support their iris cameras using the plug-in framework provided with the Device Manager from the VeriEye SDK. The integrators should note, that the most accurate iris recognition is achievable only when iris images are captured with near-infrared cameras and appropriate illumination. However, it is still possible to recognize irises with reasonable accuracy, when the irises are captured with regular cameras, using proper illumination and focus, and choosing proper environment.
  • glibc 2.24 library or newer
  • Database engine or connection with it. VeriEye templates can be saved into any DB (including files) supporting binary data saving. VeriEye Extended SDK contains the following support modules for Matching Server on Linux platform:
    • MySQL;
    • Oracle;
    • PostgreSQL;
    • SQLite.
  • Network/LAN connection (TCP/IP) for client/server applications. Also, network connection is required for using Matching server component (included in VeriEye Extended SDK). VeriEye SDK does not provide communication encryption with the Matching server, therefore, integrators should secure the communication by themselves.
  • Specific requirements for application development:
    • gcc 6.3 or newer
    • GNU Make 3.81 or newer
    • Java SE JDK 8 or newer
    • Python 3.x

Linux ARM64 platform requirements

We recommend to contact us and report the specifications of a target device to find out if it will be suitable for running VeriEye-based applications.

There is a list of common requirements for ARM Linux platform:

  • A device with ARM-based processor, running Linux 3.2 kernel or newer.
  • ARM-based 1.5 GHz processor recommended for iris processing in the specified time.
    • ARMHF architecture (EABI 32-bit hard-float ARMv7) is required.
    • Lower clock-rate processors may be also used, but the iris processing will take longer time.
  • At least 1 GB of free RAM should be available for the application. Additional RAM is required for applications that perform 1-to-many identification, as all biometric templates need to be stored in RAM for matching.
  • Iris scanner:
    • At the moment iris scanner support on ARM Linux platform should be implemented by integrators. The integrators should note, that the most accurate iris recognition is achievable only when iris images are captured with near-infrared cameras and appropriate illumination. However, it is still possible to recognize irises with reasonable accuracy, when the irises are captured with regular cameras, using proper illumination and focus, and choosing proper environment.
    • Iris images in BMP, JPG, PNG or WebP formats can be processed thus almost any third-party iris capturing hardware can be used with the VeriEye technology if it generates images in the mentioned formats.
  • glibc 2.17 or newer.
  • Network/LAN connection (TCP/IP) for client/server applications. Also, network connection is required for using Matching server component (included in VeriEye Extended SDK). VeriEye SDK does not provide communication encryption with the Matching server, therefore, integrators should secure the communication by themselves.
  • Development environment specific requirements:
    • gcc 4.8 or newer
    • GNU Make 3.81 or newer
    • Java SE JDK 8 or newer

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