VeriEye iris identification technology is designed for biometric systems developers and integrators. The technology includes many proprietary solutions that enable robust iris enrollment under various conditions and fast iris matching in 1-to-1 and 1-to-many modes.Available as a software development kit that allows development of stand-alone and Web-based solutions on Microsoft Windows, Linux, Mac OS X, iOS and Android platforms.
Neurotechnology began research and development in the field of eye iris biometrics in 1994 and has released VeriEye iris recognition algorithm in 2008. The original proprietary algorithm solves the limitations and drawbacks of existing state-of-the-art algorithms. VeriEye implements advanced iris segmentation, enrollment and matching using robust digital image processing algorithms:

• Robust Iris Detection

Irises are detected even when there are obstructions to the image, visual noise and/or different levels of illumination. Lighting reflections, eyelids and eyelashes obstructions are eliminated. Images with narrowed eyelids or eyes that are gazing away are also accepted.

• Automatic Interlacing Detection And Correction

Results in maximum quality of iris features templates from moving iris images.

• Gazing-away eyes

Are correctly detected on images, segmented and transformed as if it were looking directly into the camera (see Figure 1).

• Correct iris segmentationis obtained even under these conditions:
  • Perfect circles fail.VeriEye uses active shape models that more precisely model the contours of the eye, as iris boundaries are not modeled by perfect circles.
  • The centers of the iris inner and outer boundaries are different(see Figure 2). The iris inner boundary and its center are marked in red, the iris outer boundary and its center are marked in green.
  • Iris boundaries are definitely not circles and even not ellipses(see Figure 3) and especially in gazing-away iris images.
  • Iris boundaries seem to be perfect circles.The recognition quality can still be improved if boundaries are found more precisely (see Figure 4). Note these slight imperfections when compared to perfect circular white contours.
  • Iris is partially occluded by eyelids.The upper and lower lids are marked in red and green correspondingly (see Figure 5).
• Reliability

VeriEye 10.0 algorithm has shown excellent recognition accuracy during the NIST IREX evaluations, as well as during testing on publicly available datasets.

• Rapid and accurate iris identification, proven by NIST IREX.
• Robust recognition, even with gazing-away eyes or narrowed eyelids.
• Original proprietary algorithm solves the limitations and drawbacks of existing state-of-the-art algorithms.
• Available as multiplatform SDK that supports multiple programming languages.
• Reasonable prices, flexible licensing and free customer support.

VeriEye iris identification technology performance and reliability was proven in several NIST-organized competitions and technology evaluations.

IREX IV, IREX III and IREX Evaluations by NIST

• IREX IV – in 2013 Neurotechnology’s iris recognition algorithm has been judged the by the NIST as one of the fastest and most accurate among the participants. See our comments on IREX IV participation for more details.
• IREX III – in 2012 VeriEye iris matching algorithm was the second fastest and provided 3 times higher recognition accuracy than the only faster contender. Read more.
• IREX – in 2009 VeriEye iris matching algorithm was recognized as the fastest overall with top 3 accuracy rating and up to 7.5 times smaller template than the corresponding contenders. Read more.

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 10.0 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, Mac OS X, iOS or Android operating systems.
• VeriEye 10.0 Extended SDK is designed for biometric web-based and network 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.

The table below compares VeriEye 10.0 Standard SDK and VeriEye 10.0 Extended SDK. See the licensing model for more information on specific license types.

(1) Iris Client component includes Iris Extractor and Iris BSS components, which can be also obtained separately.

VeriEye 10.0 SDK includes programming samples and tutorials that show how to use the components of the SDK to perform iris template extraction or matching against other templates. The samples and tutorials are available for these programming languages and platforms:

VeriEye SDK includes the following biometric components for eye image capture, iris template extraction and matching, as well as biometric standards and specific image format support.

Iris Matcher Component

The Iris Matcher performs iris template matching in 1-to-1 (verification) and 1-to-many (identification) modes on PC or Mac platform.
The Iris Matcher component matches 40,000 irises per second and is designed to be used in desktop or mobile biometric systems, which run on PCs or laptops with at least Intel Core 2 Q9400 (2.67 GHz) processor. Also the Iris Matcher can be used together with Matching Servercomponent for iris matching on the server-side of a client-server system.
One Iris Matcher license is included with VeriEye 10.0 Standard SDK and VeriEye 10.0 Extended SDK. More licenses for this component can be purchased any time by VeriEye 10.0 SDK customers.

Embedded Iris Matcher Component

The Embedded Iris Matcher has the same functionality, as the Iris Matcher. It matches 3,000 irises per second and is designed to be used in embedded or mobile biometric systems, which run on ARM Linux, Android or iOS devices. The Android devices should be based on at least Snapdragon S4 system-on-chip (Krait 300 processor with 4 cores running at 1.51 GHz).One Embedded Iris Matcher license for each of Android, iOS and ARM Linux platforms is included with VeriEye 10.0 Standard SDK and VeriEye 10.0 Extended SDK. More licenses for this component can be purchased any time by VeriEye 10.0 SDK customers.

Iris Client Component

The Iris Client component is a combination of the Iris Extractor and Iris BSS components. It is designed for the systems that need to support all functionality of the mentioned components on the same PC. Using these licenses allows to optimize component license costs as well as reduce license management.
The Iris Client extracts a single iris template in 0.6 seconds. The specified performance requires a PC or laptop with at least Intel Core 2 Q9400 (2.67 GHz) processor.
Three licenses for the Iris Client component are included with VeriEye 10.0 Extended SDK. More licenses for this component can be purchased any time by VeriEye 10.0 Extended SDK customers.

Embedded Iris Client Component

The Embedded Iris Client component has the same functionality as the Iris Client and is designed to run on ARM Linux, Android or iOS devices. The Android devices should be based on at least Snapdragon S4 system-on-chip (Krait 300 processor with 4 cores running at 1.51 GHz). The component extracts a single iris template in 1.2 seconds.
Three licenses for the Embedded Iris Client component for each of Android, iOS and ARM Linux platforms are included with VeriEye 10.0 Extended SDK. More licenses for this component can be purchased any time by VeriEye 10.0 Extended SDK customers.

Iris Extractor Component

Iris Extractor creates iris templates from eye images.
The component extracts a single iris template in 1.34 seconds. The specified performance requires a PC or laptop with at least Intel Core 2 Q9400 (2.67 GHz) processor.
One Iris Extractor license is included with VeriEye 10.0 Standard SDK and VeriEye 10.0 Extended SDK. More licenses for this component can be purchased any time by VeriEye 10.0 SDK customers.

Embedded Iris Extractor Component

The Embedded Iris Extractor has the same functionality as the Iris Extractor and is designed to be run on ARM Linux, Android or iOS devices. The Android devices should be based on at least Snapdragon S4 system-on-chip (Krait 300 processor with 4 cores running at 1.51 GHz). The component extracts a single iris template in 1.34 seconds.
One Embedded Iris Extractor license for each of Android, iOS and ARM Linux platforms is included with VeriEye 10.0 Standard SDK and VeriEye 10.0 Extended SDK. More licenses for this component can be purchased any time by VeriEye 10.0 SDK customers.

Iris BSS (Biometric Standards Support) Component

The Iris BSS (Biometric Standards Support) component allows to integrate support for iris image format standards and additional image formats with new or existing biometric systems based on VeriEye SDK.
These biometric standards are supported:

• BioAPI 2.0 (ISO/IEC 19784-1:2006)(Framework and Biometric Service Provider for iris identification engine)
• CBEFF V1.2 (ANSI INCITS 398-2008)(Common Biometric Exchange Formats Framework)
• CBEFF V2.0 (ISO/IEC 19785-1:2006, 19785-3:2007)(Common Biometric Exchange Formats Framework)
• ISO/IEC 19794-6:2005(Iris Image Data)
• ISO/IEC 19794-6:2011with  1:2012
• ISO/IEC 29794-6:2015(Iris Image Data)
• ANSI/INCITS 379-2004(Iris Image Interchange Format)

Iris BSS component also allows to integrate JPEG 2000 image format support into applications based on VeriEye SDK or MegaMatcher SDK.
The component is designed for applications that run on hardware with at least Intel Core 2 Q9400(2.67 GHz) processor. It can be used from C/C++, C# and Java applications on all supported platforms. .NET wrappers of Windows libraries are provided for .NET developers.
Licenses for the Iris BSS component can be purchased anytime by VeriEye 10.0 Extended SDK customers.

There are specific requirements for each platform which will run VeriEye-based applications. Click on specific platform to view the corresponding requirements.

Microsoft Windows Platform Requirements

• Microsoft WindowsXP / Vista / 7 / 8 / 10, 32-bit or 64-bit.
• PC or laptop withx86 (32-bit) or x86-64 (64-bit) compatible processors.
  • 2 GHz or better processor is recommended.
  • SSE2 support is required. Processors that do not support SSE2 cannot run the VeriEye algorithm. Please check if a particular processor model supports SSE2 instruction set.
• At least128 MB 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. For example, 50,000 templates (each containing 2 iris records) require about 223 MB of additional RAM.
• Free space on hard disk drive (HDD):
  • at least 1 GB required for the development.
  • 100 MB required for VeriEye components deployment.
  • Additional space would be required in these cases:
    • VeriEye does not require the original eye image to be stored for the matching; only the templates need to be stored. However, storing eye irises images on hard drive for the potential future usage is recommended.
    • Usually a database engine runs on a separate computer (back-end server). However, DB engine can be installed on the same computer for standalone applications. In this case HDD space for templates storage must be available. For example, 50,000 templates (each containing 2 iris records) stored using a
    • relational database would require about 223 MB of free HDD space. Also, the database engine itself requires HDD space for running. Please refer to HDD space requirements from the database engine providers.
  • Iris Scanner:
    • VeriEye SDK includes support modules forseveral iris scanners under Microsoft Windows platform.
    • Iris images inBMP, JPG or PNG 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 writeplug-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. See our testing results for details.
  • Database engineor 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;
  • Network/LAN connection (TCP/IP)for client/server applications. Also, network connection is required for using Matching server component (included in VeriEye Extended SDK). Communication with Matching server is not encrypted, therefore, if communication must be secured, a dedicated network (not accessible outside the system) or a secured network (such as VPN; VPN must be configured using operating system or third party tools) is recommended.
  • Microsoft.NET framework 3.5 or newer (for .NET components usage).
  • One of followingdevelopment environments for application development:
    • Microsoft Visual Studio 2008 SP1 or newer (for application development under C/C++, C#, Visual Basic .Net)
    • Sun Java 1.6 SDK or later

Android Platform Requirements

• A smartphone or tablet that is runningAndroid 4.0 (API level 14) OS or newer.
  • API level 19 is the recommendedtarget for code compilation.
  • If you have a custom Android-based device or development board,contact us to find out if it is supported.
• ARM-based5 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 least20 MB 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. For example, 1,000 templates (each containing 1 iris record) require about 5 MB of additional RAM.
• Free storagespace (built-in flash or external memory card):
  • 30 MB required for embedded iris components deployment for each separate application.
  • Additional space would be required if an application needs to store original eye images. VeriEye does not require the original eye iris image to be stored for the matching; only the templates need to be stored.
• Iris scanner:
  • VeriEye SDK includes support modules for several iris scanners under Android platform.
  • Iris images inBMP, JPG or PNG 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 writeplug-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. See our testing results for details.
• Network/LAN connection (TCP/IP)for client/server applications. Also, network connection is required for using Matching server component (included in VeriEye Extended SDK). Communication with Matching server is not encrypted, therefore, if communication must be secured, a dedicated network (not accessible outside the system) or a secured network (such as VPN; VPN must be configured using operating system or third party tools) is recommended.
• PC-side developmentenvironment requirements:
  • Java SE JDK 6 (or higher)
  • Eclipse Indigo (3.7) IDE
  • Android development environment (at least API level 14 required)
  • One of the following build automation systems:
    • Apache Maven 3.1.xor newer
    • Gradle 2.10or newer
  • Internet connection for activating VeriEye component licenses

iOS Platform Requirements

• One of the following devices, runningiOS 8.0 or newer:
  • iPhone 5or newer iPhone.
  • iPad 2or newer iPad, including iPad Mini and iPad Air models.
  • iPod Touch 6th Generationor newer iPod.
• At least20 MB 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. For example, 1,000 templates (each containing 1 iris record) require about 5 MB of additional RAM.
• Free storagespace (built-in flash or external memory card):
  • 30 MB required for embedded iris components deployment for each separate application.
  • Additional space would be required if an application needs to store original iris images. VeriEye does not require the original eye iris image to be stored for the matching; only the templates need to be stored.
• 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. See our testing results for details.
  • Iris images inBMP, JPG or PNG 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). Communication with Matching server is not encrypted, therefore, if communication must be secured, a dedicated network (not accessible outside the system) or a secured network (such as VPN; VPN must be configured using operating system or third party tools) is recommended.
• Development environmentrequirements:
  • a Mac running Mac OS X 10.10.x or newer.
  • Xcode 6.4 or newer.

Mac OS X Platform Requirements

• A Mac runningMac OS X 10.7.x or newer. 2 GHz or better processor is recommended.
• At least128 MB 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. For example, 10,000 templates (each with 1 iris record) require about 25 MB of additional RAM.
• Free space on hard disk drive (HDD):
  • at least 1 GB required for the development.
  • 100 MB required for VeriEye components deployment.
  • Additional space would be required in these cases:
    • VeriEye does not require the original eye iris image to be stored for the matching; only the templates need to be stored. However, storing iris images on hard drive for the potential future usage is recommended.
    • Usually a database engine runs on a separate computer (back-end server). However, DB engine can be installed on the same computer for standalone applications. In this case HDD space for templates storage must be available. For example, 10,000 templates (each with 1 iris record) stored using a relational database would require about 25 MB of free HDD space. Also, the database engine itself requires HDD space for running. Please refer to HDD space requirements from the database engine providers.
  • Iris scanner:
    • At the moment iris scanner support on Mac OS X 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. See our testing results for details.
    • Iris images inBMP, JPG or PNG 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 engineor 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 Mac OS X 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). Communication with Matching server is not encrypted, therefore, if communication must be secured, a dedicated network (not accessible outside the system) or a secured network (such as VPN; VPN must be configured using operating system or third party tools) is recommended.
  • Specific requirements forapplication development:
    • XCode 4.3 or newer
    • wxWidgets 3.0.0 or newer libs and dev packages (to build and run SDK samples and applications based on them)
    • Qt 4.8 or newer libs, dev and qmake packages (to build and run SDK samples and applications based on them)
    • GNU Make 3.81 or newer (to build samples and tutorials development)
    • Sun Java 1.6 SDK or later

Linux x86 / x86-64 Platform Requirements

• Linux 2.6 or newer kernel (32-bit or 64-bit) is required.Linux 3.0 kernel or newer is recommended.
• PC or laptop withx86 (32-bit) or x86-64 (64-bit) compatible processors.
  • 2 GHz or better processor is recommended.
  • SSE2 support is required. Processors that do not support SSE2 cannot run the VeriLook algorithm. Please check if a particular processor model supports SSE2 instruction set.
• At least128 MB 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. For example, 10,000 templates (each with 1 iris record) require about 25 MB of additional RAM.
• Free space on hard disk drive (HDD):
  • at least 1 GB required for the development.
  • 100 MB required for VeriEye components deployment.
  • Additional space would be required in these cases:
    • VeriEye does not require the original eye iris image to be stored for the matching; only the templates need to be stored. However, storing iris images on hard drive for the potential future usage is recommended.
    • Usually a database engine runs on a separate computer (back-end server). However, DB engine can be installed on the same computer for standalone applications. In this case HDD space for templates storage must be available. For example, 10,000 templates (each with 1 iris record inside) stored using a relational database would require about 40 MB of free HDD space. Also, the database engine itself requires HDD space for running. Please refer to HDD space requirements from the database engine providers.
  • Iris scanner:
    • VeriEye SDK includes support modules for several iris scanners under Linux x86 platform.
    • Iris images inBMP, JPG or PNG 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 writeplug-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. See our testing results for details.
  • glibc 2.11.3 library or newer
  • Database engineor 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;
  • Network/LAN connection (TCP/IP)for client/server applications. Also, network connection is required for using Matching server component (included in VeriEye Extended SDK). Communication with Matching server is not encrypted, therefore, if communication must be secured, a dedicated network (not accessible outside the system) or a secured network (such as VPN; VPN must be configured using operating system or third party tools) is recommended.
  • Specific requirements forapplication development:
    • wxWidgets 3.0.0 or newer libs and dev packages (to build and run SDK samples and applications based on them)
    • Qt 4.8 or newer libs, dev and qmake packages (to build and run SDK samples and applications based on them)
    • GCC-4.4.x or newer
    • GNU Make 3.81 or newer
    • Sun Java 1.6 SDK or later
    • pkg-config-0.21 or newer (optional; only for Matching Server database support modules compilation)

ARM Linux 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, runningLinux 3.2 kernel or newer.
• ARM-based5 GHz processor recommended for iris processing in the specified time.
  • ARMHFarchitecture (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 least128 MB 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. For example, 1,000 templates (each containing 1 iris record) require about 5 MB of additional RAM.
• Free storagespace (built-in flash or external memory card):
  • 100 MB required for VeriEye components deployment.
  • Additional space would be required in these cases:
    • An application needs to store original eye / iris images. Note that VeriEye does not require the original images to be stored for the matching; only the templates need to be stored.
    • Usually a database engine runs on a separate computer (back-end server). However, a DB engine can be installed on the same device for standalone applications. For example, 1,000 templates (each with 1 iris record) stored using a relational database would require about 2.5 MB of free storage space.
      PostgreSQL, MySQL and SQLite are supported on ARM-Linux. Please refer to hardware requirements from the corresponding database engine providers.
  • 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. See our testing results for details.
    • Iris images inBMP, JPG or PNG 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 2.13 or newer.
  • libstdc++-v3 4.7.2 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). Communication with Matching server is not encrypted, therefore, if communication must be secured, a dedicated network (not accessible outside the system) or a secured network (such as VPN; VPN must be configured using operating system or third party tools) is recommended.
  • Development environmentspecific requirements:
    • GCC-4.4.x or newer
    • GNU Make 3.81 or newer
    • JDK 1.6 or later

The table below explains which eye iris scanners are supported by VeriEye SDK under different operating systems.
We are always looking for scanners’ manufacturers to include the support for their iris scanners to our products. Please, contact us for more details.
Integrators or scanner manufacturers can also write plug-ins for the Device Manager from the VeriEye SDK to support their iris cameras using the provided plug-in framework. The SDK documentation contains more information about the plug-in framework.

Notes: 
(1) Can be used on 64-bit OS, but only in 32-bit applications. 
(2) The device has pre-installed Android OS.

• 64 pixelsis the minimal radius of circle containing full iris texture, that is required for iris template extraction.
• Near-infraredspectral region is recommended for iris image capture.
• All iris templates should be loaded into RAM before identification, thus the maximum iris template database size is limited by the amount of available RAM.
• VeriEye biometric template extraction and matching algorithm is designed to run onmulti-core processors allowing to reach maximum possible performance on the used hardware.

• Notes:
  (1) Requires to be run on iOS devices or Android devices based on at least Snapdragon S4 system-on-chip with Krait 300 processor (4 cores, 1.51 GHz).
  (2) Requires to be run on PC or laptop with at least Intel Core 2 Q9400 quad-core processor (2.67 GHz) to reach the specified performance.

We present the testing results to show VeriEye 10.0 template matching algorithm reliability evaluations. Iris images from several standard datasets were used for testing, thus the testing results can be compared with testing results of other algorithms. All datasets contained iris images with 640 x 480 pixels size.

Notes:

1. The ICE2005 dataset was collected by the National Institute of Standards and Technology (NIST). Near-infrared spectrum equipment was used for iris capture. ICE2005 Exp1 is a subset, which contains right iris images.
2. The ND-IRIS-0405 was collected by the University of Notre Dame. Near-infrared spectrum equipment was used for iris capture.
3. The IRISDB1600 was collected by the University of Bath. Near-infrared spectrum equipment was used for iris capture. The full IRISDB1600 dataset contains 31,997 images (image size 1280×960 pixels), which represented 799 unique persons and 1,598 unique irises. A subset used in this test was preprocessed similar toNIST IREX experiments – the images were downsampled to 640×480 via 2×2 neighborhood averaging, and all images containing irises with diameters larger than 340 pixels were removed.
4. The MobileIrisV10 dataset was collected by the Warsaw University of Technology. The iris image collection was performed using regular,visible light spectrum camera built-in into Apple iPhone 5S  Colored images were collected with the camera. The images were resized to 640×480 pixels and converted to grayscale. See the scientific paper for more details.

Two tests were performed with each dataset:

• Test 1maximized matching accuracy. VeriEye 10.0 algorithm reliability in this test is shown as blue curves on the ROC charts.
• Test 2maximized matching speed. VeriEye 10.0 algorithm reliability in this test is shown as red curves on the ROC charts.

The iris rotation tolerance was set to ±15° in all tests.

Receiver operation characteristic (ROC) curves are usually used to demonstrate the recognition quality of an algorithm. ROC curves show the dependence of false rejection rate (FRR) on the false acceptance rate (FAR).

The following licensing model is intended for end-userproduct developers. Integrators who want to develop and sell a VeriEye-based development tool (with API, programming possibilities, programming samples, etc.), must obtain permission from Neurotechnology and sign a special VAR agreement

Product Development

An integrator should obtain either a VeriEye 10.0 Standard SDK (EUR 339) or VeriEye 10.0 Extended SDK (EUR 859) to develop a product based on VeriEye technology. The SDK needs to be purchased just once and may be used by all the developers within the integrator’s company.
VeriEye SDKs include a number of components; each particular component has specific functionality. A license for an individual VeriEye component is required for each computer or device that runthe component.

(1) Iris Client component includes Iris Extractor and Iris BSS components, which can be also obtained separately.

Components are copy-protected – a license is required for a component to run. License activation options are listed below on this page.

Additional component licenses may be obtained by VeriEye 10.0 SDK customers as required by their development process.

Product Deployment

To deploy a product developed with VeriEye 2.3 / 2.4 / 2.5 / 2.6 / 2.7 / 2.8 / 2.9 / 2.10 / 10.0 SDK, an integrator need obtain only the additional licenses required for the particular VeriEye 10.0 components that will run on each computer or device belonging to their customers. The available VeriEye components and license types for product deployment are the same as for product development.
See Product Advisor to find out what specific components will be needed for the deployment of your system.
Each VeriEye component running on a computer belonging to the integrator’s customer requires a license. License activation options are listed below on this page.
Prices for VeriEye 10.0 SDK and additional VeriEye component licenses can be found here

Licensing Agreement

The Licensing Agreement contains all licensing terms and conditions.
Note that you unambiguously accept this agreement by placing an order using Neurotechnology online ordering service or by email or other means of communications. Please read the agreement before making an order.

Single computer licenses

A single computer license allows the installation and running of a VeriEye component installation on one computer or device. Neurotechnology provides a way to renew the license if the computer undergoes changes due to technical maintenance.
Each single computer license requires activation for a VeriEye component to run. The available activation options are listed below on this page.
Additional single computer licenses for VeriEye components may be obtained at any time by VeriEye SDK customers.

License activation options

Single computer licenses are supplied in three ways:
Serial numbers are used to activate licenses for particular VeriEye components. The activation is done via the Internet or by email. After activation the network connection is not required for single computer license usage.
Notes:
Activation by serial number is not suitable for iOS and ARM-Linux platforms.
Activation by serial number is not suitable for virtual environments.
Internet activation. A special license file is stored on a computer or a mobile/embedded device; the license file allows to run particular VeriEye components on that computer or device after checking the license over the Internet. Internet connection should be available periodically for a short amount of time. A single computer license can be transferred to another computer or device by moving the license file there and waiting until the previous activation expires.
Licenses may be stored in a volume license manager dongle. License activation using volume license manager may be performed without connection to the Internet and is suitable for virtual environments.

Volume License Manager

Volume license manager is used on site by integrators or end users to manage licenses for VeriEye components. It consists of license management software and a dongle, used to store the purchased licenses. An integrator or an end-user may use the volume license manager in the following ways:

• Activating single computer licenses– An installation license for a VeriEye component will be activated for use on a particular computer. The number of available licenses in the license manager will be decreased by the number of activated licenses.
• Managing single computer licenses via a LAN or the Internet– The license manager allows the management of installation licenses for VeriEye components across multiple computers or mobile/embedded devices in a LAN or over the Internet. The number of managed licenses is limited by the number of licenses in the license manager. No license activation is required and the license quantity is not decreased. Once issued, the license is assigned to a specific computer or device on the network.
• Using license manager as a dongle– A volume license manager containing at least one license for a VeriEye component may be used as a dongle, allowing the VeriEye component to run on the particular computer where the dongle is attached.

Additional VeriEye component licenses for the license manager may be purchased at any time. Neurotechnology will generate an update code and send it to you. Simply enter the code into the license manager to add the purchased licenses.

Enterprise License

The VeriEye enterprise license allows an unlimited use of VeriEye components in end-user products for a specific territory, market segment or project. Specific restrictions would be included in the licensing agreement.
The enterprise license price depends on the application size and the number of potential users of the application within the designated territory, market segment or project.
For more information please contact us.

Licensing Old VeriEye Versions – 2.0 / 2.1 / 2.2

Existing VeriEye customers may also use the license management options provided for their version of VeriLook SDK. See VeriEye 2.0 / 2.1 / 2.2 SDK license management reference for more information.

MegaMatcher SDK – For development of AFIS or multi-biometric iris, fingerprint, face and voice identification products.
MegaMatcher On Card SDK – A product for iris, fingerprint and face matching on smart cards.