ONYX® is the world's first, most widely deployed, and most accurate touchless fingerprint biometric for mobile. Whether you're building a new biometric system or leveraging an existing platform. From finacnial inclusion to healthcare to enterprise authentication, ONYX will provide you with the ease of deployment and reliability you need.
THE ONYX® SDK IS OUR CORE SOLUTION, IT CAN BE USED FOR NATIVE IOS AND ANDROID DEVELOPMENT AND HTML5 MULTI-PLATFORM DEVELOPMENT VIA OUR ONYX CORDOVA PLUGIN. THE ONYX SDK PROVIDES CORE BIOMETRIC FUNCTIONALITY: IMAGE CAPTURE (VIA REAR-FACING CAMERA), IMAGE PROCESSING, AND ON-DEVICE ENROLLMENT AND MATCHING
In addition to basic fingerprint biometric capability, we've added some additional features:
- ONYX Live - The first and only true Liveness Detection and Anti-Spoofing (LDAS) for touchless fingerprint biometrics. ONYX Live cloud-based LDAS can accurately detect real/fake, living/deceased finger images to prevent presentation attacks.
- WSQ On-Device - Integrated into the ONYX library is the ability to perform high-speed image compression via a NIST standard Wavelet Scalar Quantization algorithm on iOS or Android.
- Image Output - ONYX contains methods to retrieve the fingerprint imagery for processing, storage, or transmission in various formats:
- Raw - The Raw Image Collected by ONYX
- Preprocessed - The grayscale Fingerprint
- Enhanced - The Preprocessed Image with our Proprietary Enhancement Algorithm Applied
- Black & White - The Preprocessed Image in Black & White.
- AFIS Interoperability - The ONYX SDK provides several functions to facilitate integration with third-party on-server matching algorithms, and matching against enrollments from touch-based sensors, commonly found in an AFIS environment
- Image Inversion - Inverts ridge/valley color to orient the coloring the same as touch-based fingerprints
- Image Flipping - Provides a mirror image of the fingerprint to orient the image the same as touch-based fingerprints
- Image Pyramiding - Creates scaled/up or down versions of the collected image to match the scale of touch-based imagery in existing database.