Securing your identity with MobileIrisID
Iris recognition Android app
Embed iris capture right into the apps or use our pre-built one
Download the MobileIrisID app from Google Play to see how it works
Fraud and fool detection
Built-in fraud detection catches glass eyes, photos or unresponsive people
Cloud identity platform
Comprehensive cloud services for identity management, integration and additional fraud detection
On-premise, private cloud or public cloud
Designed for innovators
Software developer or business developer > sign-up and go.
Full set of APIs and an Android SDK for embedding.
Iris verification is more secure than fingerprint scanners
Powerful fraud and fool prevention
Enterprise to home uses
Executive authorization of high-value transactions
Door access control by combining iris verification with NFC access
Document access by integrating to enterprise document management systems like Sharepoint or Dropbox
Electronic signature verification for contracts
Two-factor authentication for accessing bank information
Customer support verification so call agents don’t rely on SSN or zip code
Open house door without a key
Start car or open remotely without worrying about losing keys
Health Record access and other personal information
Frequently Asked Questions
Why does MobileIrisiD use visible light (VL) while others primarily use near infrared light (NIR)?
Due to a couple of factors, it’s easier to capture a person’s iris using NIR instead of VL. One major reason is lighting. To capture a high-quality picture of the iris, you need adequate direct lighting that will reveal enough details while drowning out ambient light. Infrared light (IR) does not stimulate the photoreceptors in the human eye, therefore a very bright IR light can be shined into the eye without discomfort to the person. This luxury is not available to phones unequipped with dedicated NIR lights and NIR cameras.
The Samsung Note 7 is the first popular consumer phone on the market to offer NIR. Microsoft 950 XL and HP Elite x3 also offer it, but are Windows Mobile phones tailored towards enterprise clients. MobileIrisID is focused on creating a technology that reaches a broader customer base. There are more phones on the market that can support VL iris scanning than there are with NIR support.
MobileIrisID supports two modes, one is through the front camera and other is through the back camera. The minimum requirement for iris identification is an 8MP sensor, meaning almost all smartphones today have the capability to use MobileIrisID. The patented barcode projection technology is an added benefit for those phones that have a high enough front camera.
What is gained/lost by doing iris recognition in VL instead of NIR?
Iris recognition relies on capturing patterns formed by various melanin pigments and connective tissue of the anterior layer and stroma. NIR and VL gets absorbed/scattered by the iris differently, with NIR focusing on texture while VL focusing on pigmentation. Both NIR and VL can provide enough information about the iris to uniquely identify a person. Ultimately, commercial iris recognition algorithms rely on grey scale images regardless of what spectrum they were captured in.
With VL, a person with brown eyes has to hold the camera closer or have more light shined in than a person with blue eyes. For NIR, the distance is the same for all eye colors.
The major difference between NIR and VL is that darker eyes have more melamine, which reflect VL but let NIR pass through. This results in NIR penetrating the iris slightly more that reveal texture not easily observed in the VL spectrum. But NIR imaging cannot distinguish the effects of melanin, the primary coloring component of the iris.
What other benefits does VL provide?
MobileIrisID capitalizes on eye color in ways that NIR can’t. For security reasons, no product (VL or NIR) ever keeps a captured iris image on the phone or the server. Instead, an iris is “serialized” into a template in such a way that it can’t be transformed back into the original image. Every time someone captures their iris, it’s serialized in the same way and compared to a list of templates. If the list of serialized irises are stolen from the database, it may require rebuilding the entire serialization algorithm to render the stolen ones useless.
MobileIrisID adds a unique step of shifting the hue/saturation of the iris before it converts to greyscale, which then produces a different serialization. For example, making a blue eye more green. If MobileIrisID suspects foul play, it simply sets a new shifting policy which automatically make the stolen templates useless. A request is automatically sent to every user to re-register.