Key Features:
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Why They Matter:
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| Fingerprint Feature Extractor - generates fingerprint minutiae data (also referred to as a fingerprint template) from fingerprint images. |
Converts bulky fingerprint images into small, mathematical representations for efficient storage and comparison. |
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| 1-Many Identification - searches a collection of fingerprint templates to identify users based on their fingerprint. |
Enables applications to identify users by their fingerprint, making sign-on and approval operations quick and easy to use. |
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| 1-1 Verification - compares two fingerprint templates to determine if they represent the same fingerprint. |
Enables applications to quickly verify that a user’s fingerprint matches a previously-sampled template. |
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| Capture-Device Independent - works with 8 bits-per-pixel grayscale fingerprint image data from any source, formatted in a simple pixel array. |
Enables apps to use appropriately-formatted fingerprint images from any brand of fingerprint reader or fingerprint image database. |
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| Commercially-Licensed - designed for incorporation into devices and applications. |
Gives software and hardware developers advanced technology that they can use in commercial applications. |
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| Source or Binary - offered in either source code or binary form. |
Provides flexibility for manufacturers or application writers. |
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| Portable - written in self-contained C++ to run on Linux, Android, Windows, Windows CE, various real-time OSes or environments without an OS. |
Can be used across many different environments, eliminating the need for different and incompatible extractor technologies on each platform. |
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| Flexible - works on 32-/64-bit CPUs as well as 32-bit microcontrollers; no DSP or floating point required. |
Can be integrated quickly and easily into devices and applications without requiring special hardware. |
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| Compact - uses approximately 192k of code space (can be run from ROM) and 128k data space (32k plus the size of the image buffer, which is one byte per pixel). |
Makes high-quality biometrics efficient even in memory-constrained embedded devices. |
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| Scalable - runs well on embedded chips, desktop computers, even large servers. |
Generates consistent, reliable biometric data for applications across many different platforms. |
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| Standards - uses 8 bits-per-pixel grayscale image data in simple pixel array format; generates and matches ANSI INSITS 378-2004 or ISO/IEC 19794-2:2005 fingerprint minutiae data. |
Ensures that fingerprint minutiae data can be exchanged with different applications and databases. |
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| MINEX-Certified Extraction - meets and exceeds the PIV requirements for fingerprint template interoperability and compliance tested by NIST in its MINEX ongoing test (SDK 3F). |
Enables applications and devices to comply with international biometrics standards that help to ensure interoperability with different back-end databases and systems. |
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| Fast Extraction - can extract fingerprint minutiae from an image in 10-25 milliseconds on an Intel i7 or 0.5-1.25 seconds on a 150MHz ARM Cortex-M3. |
Delivers excellent user response time for embedded devices and high throughput where fingerprint feature extraction is done on servers. |
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| Fast Identification - can do 5,000-10,000 templates/second on a 4-core Intel i7 CPU and 20-50 templates/second on a 150MHz ARM Cortex-M3. |
Delivers excellent user response time for embedded devices and high performance for back-end de-duplication on database servers. |
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| Fast Verification - can do 1,000-4,000 verifications/second on 4-core Intel i7 CPU and 2-10 verifications/second on a 150MHz ARM Cortex-M3. |
Delivers excellent user response time for authenticating users on small devices as well as large servers. |
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| Easy - many operations can be performed in as little as one function call. |
Enables applications to add high-quality biometric capabilities quickly. |
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