Introducing the future
● smartphones ● tablets ● laptops ● AR/VR headsets ● cars ● payment terminals ● ATMs ● access control ● time and attendance ● IoT devices
The human palm is a complex set of skin lines and creases that is unique enough to identify an individual
When a palm is placed in front of a camera from a distance of around six inches (15 cm) even a low-end camera such as ones already installed in phones, laptops and ATMs can capture the palm skin in great detail
Once captured the biometrics pipeline is a two stage process: - The PalmID® Capture Module uses sophisticated machine vision techniques to turn the RGB video input stream into an authentication-ready palm image. - The PalmID® Matching Module matches in real time the captured palm image against stored references. This process uses proprietary algorithms extensively tested against large datasets of palm images that ensure no false positives. Depending on the security model required, this process can be run on a remote server or locally
PalmID® meets the authentication needs for a wide range of markets, and is a high-performance solution for nearly any application with a standard camera. Among the many markets where PalmID is effective are:
PalmID® benefits from an enormous market opportunity: with 600 million entry-level phones, 700 million desktops, laptops and tablets and 105 million AR/VR products devices in users' hands, the camera enabled device market is wide open for adopting palm based biometrics today. With an addition, 40 billion online transactions take place each year the need for enhanced security will continue to grow dramatically in next five years.
PalmID® is supported by a team with decades of experience in computer vision and biometrics.
Kevin serves as the director of engineering. He is a machine learning expert with versatile experience in several engineering fields. Prior to Redrock, Kevin held engineering and management positions at Google and Leap Motion.
He earned his B.S. in Electrical Engineering and Computer Science from University of California Berkeley.
Before co-founding Redrock Biometrics, Hua was the director of research at Leap Motion, a motion tracking/human computer interaction system, and held an engineering position at Kitware, an open source computer graphics and imaging software company.
Hua earned a M.S. in Artificial Intelligence from the Chinese Academy of Sciences, and a Ph.D. in Computer Science from the University of North Carolina at Chapel Hill.
Lenny is a co-founder of Redrock Biometrics. He started his career in academia and continued it in Smith-Kettlewell Eye Research Institute studying human vision. Later on he became an enterpreneur founding two startups, one in image search and another digital coupons areas. Lenny met Hua while working at LeapMotion.
He holds a M.Sc. in Computer Science and Ph.D. in Physics and Mathematics from the Moscow Institute of Physics and Technology.
Chris serves as senior vice president of business development. He recently guided the growth and exit of three successful startups, including EyeVerify, where he assisted the company's growth and acquisition by Ant Financial/Alipay; and Vlingo, which was acquired in 2012 by Nuance.
Chris earned a B.S. in Economic and Finance from Columbia University and an M.B.A. in Information Systems & Marketing from Loyola University.
Nikoloz is the director of product design. Prior, he was vice president of design at Something to Talk About Media LLC. Earlier, he was a UI/UX designer at KaChing! and a graphic designer at Kommersant newspaper.
He earned a M.S. in Systems Engineering from Moscow State Aviation Technological University.
Sergei started working for Redrock Biometrics as an independent consultant and then joined the team. Before that he was an area sales manager for a subsidiary of Textron, a Fortune 500 company. In Textron he was the Best Sales Person of the Year and his team was awarded Best Region of the Year. Sergei personally supervised the largest order and 90% market share in key segments for his company.
He holds a B.S. in Genetics from University of California, Davis.
Redrock Biometrics’ innovative PalmID solution is rapidly gaining market acceptance and adoption by organizations in a wide range of industries. Please check back for regular updates on development and industry coverage.
“…the subject of the testing was PalmID, Redrock’s Artificial Intelligence-powered software designed to leverage a high-resolution camera with an LED or flash light in order to take high-quality palm images for biometric authentication.
Epson’s MOVERIO AR Smart Glasses have integrated Redrock Biometric’s PalmID into their AR platform. This collaboration introduces a biometric authentication solution for a consumer AR headset.
Redrock Biometrics and Epson bring palm print authentication to the MOVERIO smart glasses platform.
PalmID(R) Passes Level 1 PAD Conformance Testing by iBeta.
PalmID-X delivers palm-based biometrics via SaaS for large-scale identification projects.
Epson MOVERIO® Smart Glasses users can get to work or play in a flash with PalmID, the first biometric authentication solution for a consumer AR headset. PalmID’s SDK enables MOVERIO developers to build AR applications and brings new revenue opportunities to those developers.
Redrock Biometrics: Robust Security in the Palm of Your Hand.
Palm biometrics is a secure, user-friendly authentication technology, with powerful security advantages for devices ranging from smartphones to tablets to laptops to virtual reality headsets.
Why palm-based authentication?
Biometric authentication – reading the user's unique physical features to allow access to electronic devices ranging from smartphones to tablets to Smart TVs to AR/VR headsets and beyond – is the wave of the future, and no physical gesture is easier or more natural than a wave of the hand.
No new hardware required
Basic palm-based authentication is one of the easiest to integrate and use authentication systems available today, and it works on any camera-equipped device – no new hardware required. Giving a device with a camera adding palm-reading capability is simple a matter of installing software.
The leader in palm-based authentication
Redrock Biometrics is the leader in palm-based authentication technology. Our patented solution enables any camera-equipped device to read the user's unique palm print – even under low-light conditions (the light from as little as a cellphone screen is enough to capture an accurate palm image)
The security level can be strengthened even more on devices with higher-resolution RGB cameras with adaptive focus (phone-back camera). A combination of RGB and IR cameras, such as Windows Hello cameras on laptops, can be integrated for further layers of security.
Find out how powerful and effective palm-based authentication really is. Contact us today for a free demo.