System 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

• 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

• 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.

• 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 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

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