Iris recognition in the context of "Facial recognition system"

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⭐ Core Definition: Iris recognition

Iris recognition is an automated method of biometric identification that uses mathematical pattern-recognition techniques on video images of one or both of the irises of an individual's eyes, whose complex patterns are unique, stable, and can be seen from some distance. The discriminating powers of all biometric technologies depend on the amount of entropy they are able to encode and use in matching. Iris recognition is exceptional in this regard, enabling the avoidance of "collisions" (False Matches) even in cross-comparisons across massive populations. Its major limitation is that image acquisition from distances greater than a meter or two, or without cooperation, can be very difficult. However, the technology is in development and iris recognition can be accomplished from even up to 10 meters away or in a live camera feed.

Retinal scanning is a different, ocular-based biometric technology that uses the unique patterns on a person's retina blood vessels and is often confused with iris recognition. Iris recognition uses video camera technology with subtle near infrared illumination to acquire images of the detail-rich, intricate structures of the iris which are visible externally. Digital templates encoded from these patterns by mathematical and statistical algorithms allow the identification of an individual or someone pretending to be that individual. Databases of enrolled templates are searched by matcher engines at speeds measured in the millions of templates per second per (single-core) CPU, and with remarkably low false match rates.

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👉 Iris recognition in the context of Facial recognition system

A facial recognition system is a technology potentially capable of matching a human face from a digital image or a video frame against a database of faces. Such a system is typically employed to authenticate users through ID verification services, and works by pinpointing and measuring facial features from a given image.

Development on similar systems began in the 1960s as a form of computer application. Since their inception, facial recognition systems have seen wider uses in recent times on smartphones and in other forms of technology, such as robotics. Because computerized facial recognition involves the measurement of a human's physiological characteristics, facial recognition systems are categorized as biometrics. Although the accuracy of facial recognition systems as a biometric technology is lower than iris recognition, fingerprint image acquisition, palm recognition or voice recognition, it is widely adopted due to its contactless process. Facial recognition systems have been deployed in advanced human–computer interaction, video surveillance, law enforcement, passenger screening, decisions on employment and housing, and automatic indexing of images.

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Iris recognition in the context of Biometric identification

Biometrics are body measurements and calculations related to human characteristics and features. Biometric authentication (or realistic authentication) is used in computer science as a form of identification and access control. It is also used to identify individuals in groups that are under surveillance.

Biometric identifiers are the distinctive, measurable characteristics used to label and describe individuals. Biometric identifiers are often categorized as physiological characteristics which are related to the shape of the body. Examples include, but are not limited to fingerprint, palm veins, face recognition, DNA, palm print, hand geometry, iris recognition, retina, odor/scent, voice, shape of ears and gait. Behavioral characteristics are related to the pattern of behavior of a person, including but not limited to mouse movement, typing rhythm, gait, signature, voice, and behavioral profiling. Some researchers have coined the term behaviometrics (behavioral biometrics) to describe the latter class of biometrics.

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Iris recognition in the context of Retinal scan

A retinal scan is a biometric technique that uses unique patterns on a person's retina blood vessels. It is not to be confused with other ocular-based technologies: iris recognition, commonly called an "iris scan", and eye vein verification that uses scleral veins.

The human retina is a thin tissue made up of neural cells that is located in the posterior portion of the eye. Because of the complex structure of the capillaries that supply the retina with blood, each person's retina is unique, making retinal scans an emerging authentication method. The network of blood vessels in the retina is not entirely genetically determined and thus even identical twins do not share a similar pattern.

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Iris recognition in the context of FIDO2 Project

The FIDO (Fast IDentity Online) Alliance is an open industry association launched in February 2013 whose stated mission is to develop and promote authentication standards that "help reduce the world’s over-reliance on passwords". FIDO addresses the lack of interoperability among devices that use strong authentication and reduces the problems users face creating and remembering multiple usernames and passwords.

FIDO supports a full range of authentication technologies, including biometrics such as fingerprint and iris scanners, voice and facial recognition, as well as existing solutions and communications standards, such as Trusted Platform Modules (TPM), USB security tokens, embedded Secure Elements (eSE), smart cards, and near-field communication (NFC). The USB security token device may be used to authenticate using a simple password (e.g. four-digit PIN) or by pressing a button. The specifications emphasize a device-centric model. Authentication over an insecure channel happens using public-key cryptography. The user's device registers the user to a server by registering a public key. To authenticate the user, the device signs a challenge from the server using the private key that it holds. The keys on the device are unlocked by a local user gesture such as a biometric or pressing a button.

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