Face verification, in the simplest of terms, can be the routine task of a passport control comparing whether your passport photo matches your actual face.
Face recognition is a category of biometrics software that maps facial features and vectors mathematically, stores said data, and matches it to a pre-enrolled individual or to a scanned proof of identity. In the face verification process, the software uses deep learning algorithms to cross-reference a live capture with a digital image – or vice versa – in order to verify an individual’s identity.
The need and use for technology that enables face verification has a variety of purposes. Perhaps you already use face verification to unlock your phone which protects your personal and sensitive data and ensures that it remains inaccessible if your phone is stolen. Online banking activities are another everyday area for face verification, many people are accustomed to authorizing transactions by looking at their smartphone or computer. Face verification is a biometric identification solution that is used in a variety of online interactions and transactions and its uses are constantly expanding and evolving as digital customers and online services continuously increase. Another large and growing number of application areas for face verification can be in embedded system solutions. Vehicles, locks, access control systems, and everyday technology in the home are just some examples of applications. There is a growing need to easily and quickly identify individuals, for example for access control systems at airports, hospitals, and workplaces.
Face recognition systems comprise of high-end hardware components which in conjunction with proficient software use several measurements and techniques to scan faces, including thermal imaging, 3D face mapping, the cataloging of unique features, analysis of geometric proportions of facial features, mapping of distances between important facial functions and analysis of skin surface. The face recognition technology of today has nearly absolute precision, reaching a 99,7% recognition accuracy level for face verification.
Face recognition benefits and risks
As more human interactions and transactions occur online, face verification is crucial to enable efficient and accurate digital identification processes. For us humans face recognition is probably considered to be the most natural of all biometric measurements since we recognize each other’s faces rather than by looking at each other’s fingerprints or irises, for example. Further benefits with face recognition are its fast processing and non-invasive nature since it doesn’t need any contact with the individual. Manual identification of a person takes a huge amount of time and doesn’t guarantee high accuracy. With face recognition technology the process of verification merely takes a second whilst also being incredibly accurate. The technology is also easy to deploy and implement as most face recognition solutions are compatible with most of the security software and hardware used today.
In the digital world of financial activities, online banking and services face recognition plays a key role in identity verification offering security across all online interactions and transactions. Today many customers are opting for digital KYC (Know Your Customer) for their banking matters, utilizing face recognition technology resulting in fast KYC verification from the comfort of their home. But secure systems for data storage are paramount as the risks involved with the storage of biometric data is a critical issue, numerous information security incidents compromise the data of millions of users every year.
The benefits of face recognition technology carry considerable weight for improved public security and law enforcement. Face recognition in surveillance techniques and criminal databases to identify criminals are some potential areas of use. However, the need for effective law enforcement must be weighed against the protection of personal integrity. The risks of a big brother society should be considered in a just and democratic procedure. Although its benefits are many, the use of face recognition systems in the public sphere threatening to privacy and personal freedoms, non-secure biometric data storage, and potential flaws in the technology are some of the arguments against its use.
Liveness detection – that extra layer of security
Liveness detection grants the face recognition system the capacity to determine if it is dealing with a physically present human being or an inanimate spoof artifact, video, or some other imitation. At a physical encounter, such an attempt at fraud would probably be quite difficult to pull off. However, without liveness detection, it’s been proven possible in some cases to bypass a cell phone with facial recognition technology using a 3D printed mask, for example. And in the digital world attempts at identity theft and fraud occur daily. Thus, in automated and unsupervised authentication situations liveness detection is required to prevent these attempts from being successful. Its algorithms are designed in such a way that liveness detection requires very little or no user cooperation during the face recognition process.