指纹识别SDK

• VeriFinger SDK

VERIFINGER SDK
FINGERPRINT IDENTIFICATION FOR STAND-ALONE OR WEB SOLUTIONS
VeriFinger is a fingerprint identification technology designed for biometric systems developers and integrators. The technology assures system performance with fast, reliable fingerprint 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.

VERIFINGER SDK
用于单机系统或WEB解决方案的指纹识别
VeriFinger是生物识别系统开发人员和集成商适用的指纹识别技术。该技术在1：1和1：N模式下，均可快速、可靠的指纹匹配，保证系统的高性能.
作为软件开发工具包，它允许在Microsoft Windows、Linux上开发独立和基于Web的解决方案，兼容Mac OS X、iOS和Android平台。

FEATURES AND CAPABILITIES

• 1500+ end-user product brands in 100+ countries used the VeriFinger algorithm over the past 21 years.
• Full NIST MINEX compliance, FpVTE and FVC awards since 2000.
• Rolled and flat fingerprint matching that is tolerant to fingerprint translation, rotation and deformation.
• Compact fingerprint template and unlimited database size.
• Available as multiplatform SDK that supports multiple scanners and multiple programming languages.
• Reasonable prices, flexible licensing and free customer support.

产品特点和功能

• 在过去21年中，100多个国家1500+终端用户产品品牌使用了VeriFinger算法。
• 完全遵守NIST MINEX、2000年以来每年均获FpVTE和FVC荣誉。
• 兼容滚动和按捺的指纹匹配，容忍指纹的平移、旋转和变形。
• 紧凑的指纹模板和无限制的数据库大小。
• 支持多种扫描器和多种编程语言的多平台SDK。
• 合理的价格，灵活的许可和免费的客户支持。

In 1998 Neurotechnology developed VeriFinger, a fingerprint identification technology designed for biometric system integrators. Since that time, Neurotechnology has released more than 10 major and minor versions of the VeriFinger, providing most powerful fingerprint recognition algorithms to date. Numerous awards in competitions and technology evaluations, including FVC and FpVTE, have been received by VeriFinger.
The VeriFinger algorithm is based on deep neural networks and follows the commonly accepted fingerprint identification scheme, which uses a set of specific fingerprint points (minutiae) along with a number of proprietary algorithmic solutions that enhance system performance and reliability. Some are listed below:

• Rolled and flat fingerprints matching. The VeriFinger algorithm matches flat-to-rolled, flat-to-flat or rolled-to-rolled fingerprints with a high degree of reliability and accuracy, as it is tolerant to fingerprint deformations. Rolled fingerprints have much bigger deformation due to the specific scanning technique (rolling from nail to nail) than those scanned using the "flat" technique. Conventional "flat" fingerprint identification algorithms usually perform matching between flat and rolled fingerprints less reliably due to the mentioned deformations of rolled fingerprints.
• Tolerance to fingerprint translation, rotation and deformation. VeriFinger's proprietary fingerprint template matching algorithm is able to identify fingerprints even if they are rotated, translated, deformed and have only 5 - 7 similar minutiae (usually fingerprints of the same finger have 20 - 40 similar minutiae) and matches up to 40,000 flat fingerprints per second (see technical specifications for more details).
• Identification capability. VeriFinger functions can be used in 1-to-1 matching (verification), as well as 1-to-many mode (identification).
• Image quality determination. VeriFinger is able to ensure that only the best quality fingerprint template will be stored into database by using fingerprint image quality determination during enrollment.
• Adaptive image filtration. This algorithm eliminates noises, ridge ruptures and stuck ridges for reliable minutiae extraction – even from poor quality fingerprints – with a processing time of 0.6 seconds.
• Features generalization mode. This fingerprint enrollment mode generates the collection of generalized fingerprint features from a set of fingerprints of the same finger. Each fingerprint image is processed and features are extracted. Then the features collection set is analyzed and combined into a single generalized features collection, which is written to the database. This way, the enrolled features are more reliable and the fingerprint recognition quality considerably increases.
• Compact fingerprint template. VeriFinger allows to configure the number and size of fingerprint features in a fingerprint template. Combined with unlimited database size, this capability allows to optimize target system size and performance.
• Scanner-specific algorithm optimizations. VeriFinger 11.0 includes algorithm modes that help to achieve better results for the supported fingerprint scanners.

1998年，神网科技有限公司开发了VeriFinger指纹识别技术，专为生物识别系统集成商服务。从那时起，我们已经发布了10多个主要和次要版本的VeriFinger，提供了迄今为止最强大的指纹识别算法。在比赛和技术评估方面获奖无数，包括FVC和FpVTE。
VeriFinger算法基于深度神经网络，采用了常用的指纹识别方案，使用特定的指纹点(细节点)和一些专有的算法解决方案，提高了系统的性能和可靠性。特点如下：

• 兼容滚动和平捺指纹匹配。VeriFinger算法具有很高的可靠性和准确性，因为它可以容忍指纹的变形。滚动指纹由于特定的扫描技术(从指甲的一侧滚动到另一侧)的变形要比使用平捺技术的指纹要大得多。传统的平捺指纹识别算法会由于滚动指纹的变形，通常对平捺指纹和滚动指纹之间的匹配不那么可靠。
• 对指纹平移、旋转和变形的容忍度。VeriFinger的专有指纹模板匹配算法能够识别指纹，即使它们被旋转、转换、变形，并且只有5-7个相似的细节(通常同一手指的指纹有20-40相似的细节)，并且匹配多达每秒4万枚平捺指纹。
• 识别能力VeriFinger函数可以用于1对1匹配(验证)以及一对多模式(识别)
• 图像质量测定VeriFinger能够保证在注册过程中，通过指纹图像质量的确定，只将************的指纹模板存储到数据库中。
• 自适应图像过滤 该算法消除了噪声，脊破裂和粘脊，提供可靠的细节提取——即使是从劣质指纹中提取——处理时间为0.6秒。
• 特征归一化模式 该指纹注册模式从同一手指的一组指纹中生成广义指纹特征集合。对每个指纹图像进行处理，提取特征。然后对特征集进行分析，并将其组合成一个单一的广义特征集合，并将其写入数据库。这样，登记的特征更加可靠，指纹识别质量大大提高。
• 紧凑的指纹模板。VeriFinger允许在指纹模板中配置指纹特征的数量和大小。结合无限数据库大小，此功能允许优化目标系统的大小和性能。
• 特定于扫描仪的算法优化。VeriFinger 11.0包含为许多推荐指纹扫描器的图像特别优化参数。

• FingerCell SDK

FINGERCELL SDK
FINGERPRINT IDENTIFICATION FOR EMBEDDED PLATFORMS
FingerCell technology is designed for embedded biometric systems developers and features compact, sensor-independent and cross-platform fingerprint recognition algorithm. It offers decent performance on various embedded devices based on low-power microcontrollers or processors.
FingerCell is available for integrators as Software Development Kits (SDK) with FingerCell library or source code for developing a fast and reliable system on embedded or mobile platform.

FINGERCELL SDK
嵌入式指纹识别SDK
FingerCell技术是为嵌入式生物识别系统开发人员和特性设计的。紧凑型、与传感器无关和跨平台指纹识别算法。它基于低功耗微控制器或处理器的各种嵌入式设备，提供了与硬件相称的良好性能，。
FingerCell为集成商提供软件开发工具包(SDK)，也可提供FingerCell库或源代码，用于在嵌入式或移动平台上开发快速可靠的系统。

FEATURES AND CAPABILITIES

• Fast performance even on low speed processors.
• Verification (1-to-1 matching) and identification (1-to-many matching) are provided.
• Compact fingerprint template and unlimited database size.
• ANSI and ISO biometric standards support.
• Cross platform algorithm with compact portable source code.
• FingerCell Demo Unit with pre-installed algorithm is optionally available.
• Reasonable prices, flexible licensing and free customer support.

产品特点和功能

• 即使在低速处理器上，性能也够快。
• 提供验证(1：1匹配)和标识(1：N匹配).
• 紧凑的指纹模板和无限制的数据库大小。
• ANSI和ISO生物识别标准支持。
• 跨平台算法与紧凑的源代码。
• Fingercell演示单元与预装算法随时可以提供。
• 合理的价格，灵活的许可和免费的客户支持。

FingerCell is designed to provide decent reliability and identification speed for various embedded devices and platforms. The FingerCell algorithm includes these proprietary solutions:

• Fast performance. Fingerprint template extraction from an image and verification against another template can be performed in less than less than 0.7 seconds on a 168 MHz ARM Cortex-M4family processor, which is acceptable for embedded systems.
• Identification ability. FingerCell is suitable not only for fingerprint verification (1-to-1 matching), but also for identification (1-to-many matching). The algorithm matches about 250 fingerprints per second in 1-to-many mode on a 168 MHz ARM Cortex-M4 family processor.
• Adaptive image filtration. This algorithm eliminates noises, ridge ruptures and stuck ridges for reliable minutiae extraction even from poor quality fingerprints.
• Compact fingerprint template. FingerCell template size depends on the number of stored minutiae – for example, a template with 16 minutiae needs only 152 bytes of memory, whereas a template with 64 minutiae needs 448 bytes. Combined with configurable maximal number of minutiae in a template and unlimited database size, the target system size and performance can be optimized according to customers requirements.
• ANSI and ISO/IEC standards support. FingerCell SDK can generate and match fingerprint templates in the ISO/IEC 19794 and ANSI/INCITS 378 family formats
• Tolerance to fingerprint translation and rotation. Such tolerance is achieved by FingerCell proprietary fingerprint matching algorithm. The algorithm is able to identify fingerprints even if they are rotated and translated.
• Compact portable software. FingerCell is designed for easy implementation into very various and specific applications. The algorithm's source code is sensor independent; therefore it can be ported to various platforms and hardware. Compiled code and internal data arrays require only 128 kB of memory and therefore can be implemented in low memory microchips, thus reducing hardware costs.
• FingerCell Demo Unit. Neurotechnology offers pre-installed FingerCell algorithm on testing hardware for the technology evaluation. The Demo Unit is available on request.

FingerCell旨在为各种嵌入式设备和平台提供良好的可靠性和识别速度。FingerCell算法包括以下专有解决方案：

• 性能很快 从图像中提取指纹模板并对另一个模板进行验证可以在少于0.7秒内完成（168兆ARM Cortex-M4系列处理器），这是可接受的嵌入式系统。
• 识别能力 FingerCell不仅适用于指纹验证(1：1匹配)，也适用于识别(1对多匹配).该算法与每秒250个指纹（168兆的ARM Cortex-M4系列处理器上），以1对多模式运行.
• 自适应图像过滤该算法消除了噪声、脊线破裂和粘脊，即使从质量较差的指纹中提取细节信息也是可靠的。
• 紧凑的指纹模板。FingerCell模板大小取决于存储的细节数-例如，带有16个特征点的模板只需要152个字节，而一个64特征点的模板需要448字节。结合模板中可配置的******细节数和无限数据库大小，目标系统的规模和性能可以根据客户的要求进行优化。
• ANSI和ISO/IEC标准支持  FingercellSDK可以在ISO/IEC 19794和Ansi/INCITS 378系列格式和标准。
• 对指纹平移和旋转的容忍度。这种公差是通过Fingercell专有指纹匹配算法实现的。该算法能够识别指纹，即使指纹是旋转和平移的。
• 紧凑的便携式软件。FingerCell的设计是为了将其简单地实现到非常多样化和特定的应用程序中。算法的源代码是独立于传感器的，因此它可以移植不同的平台和硬件。编译的代码和内部数据数组只需要128 kB内存因此可以在低内存微芯片上实现，从而降低硬件成本。
• Fingercell演示单元。神经技术提供硬件测试中的FingerCell预装算法用于技术评估。演示股可根据要求提供。

• Free Fingerprint Verification SDK

FREE FINGERPRINT VERIFICATION SDK
Free Fingerprint Verification software development kit is a freeware SDK designed for adding fingerprint verification functionality into various applications. The SDK is most suitable for developing biometric logon applications, but it can be used also for any other application that do not require to store more than 10 fingerprints.
The Free Fingerprint Verification SDK functionality allows reading fingerprints from scanners and performing fingerprint verification (1:1 matching) only. Quality control can be applied to accept only good quality fingerprints from fingerprint scanners.

免费的指纹验证SDK
免费指纹验证软件开发工具包是一套免费软件SDK。为在各种应用程序中添加指纹验证功能而设计的。SDK最适合开发生物识别登录应用程序，但也可以用于任何不需要存储超过10个指纹的其他应用程序。
自由指纹验证SDK功能允许从扫描仪读取指纹并执行指纹验证(1：1匹配)。指纹图像质量控制保证只接受良好质量指纹。

FEATURES AND CAPABILITIES

Free Fingerprint Verification SDK allows to develop biometric applications that verify a scanned fingerprint against a previously stored fingerprint (1-to-1 matching). The SDK is based on the same technology as VeriFinger SDK. The difference is that the VeriFinger SDK is a commercial SDK that offers much more capabilites for software developers.
Free Fingerprint Verification SDK does not allow to develop applications that read fingerprint images from files or perform fingerprint identification (1-to-many matching). The number of stored fingerprint templates is limited to 10 records in the application's database.
The VeriFinger SDK contains a wrapper that allows easy transition from Free Fingerprint Verification SDK to VeriFinger SDK.
The table below shows the differences between Free Fingerprint Verification SDK and Verifinger SDK:

产品特点和功能
免费指纹验证SDK允许开发生物识别应用程序，用于验证一个新扫描指纹与先前存储的指纹库的匹配。该SDK基于与VeriFinger SDK的相同技术。不同之处在于，VeriFinger SDK是一个商业SDK，可以为软件开发人员提供了更多的能力。
免费指纹验证SDK不允许开发从文件中读取指纹图像或执行指纹识别(一对多匹配)的应用程序。在应用程序的数据库中存储的指纹模板数目限定为10枚以内。
VeriFinger SDK包含一个包装器，以便客户方便容易地从免费指纹验证SDK过渡到VeriFinger SDK。

下表显示了免费指纹验证SDK和Verifinger SDK之间的区别：