Biometrics in the context of "Facial recognition system"

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⭐ Core Definition: Biometrics

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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👉 Biometrics 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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In this Dossier

Biometrics in the context of Plant domestication

Plant breeding started with sedentary agriculture, particularly the domestication of the first agricultural plants, a practice which is estimated to date back 9,000 to 11,000 years. Initially, early human farmers selected food plants with particular desirable characteristics and used these as a seed source for subsequent generations, resulting in an accumulation of characteristics over time. In time however, experiments began with deliberate hybridization, the science and understanding of which was greatly enhanced by the work of Gregor Mendel. Mendel's work ultimately led to the new science of genetics. Modern plant breeding is applied genetics, but its scientific basis is broader, covering molecular biology, cytology, systematics, physiology, pathology, entomology, chemistry, and statistics (biometrics). It has also developed its own technology. Plant breeding efforts are divided into a number of different historical landmarks.

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Biometrics in the context of Mathematical science

The Mathematical Sciences are a group of areas of study that includes, in addition to mathematics, those academic disciplines that are primarily mathematical in nature but may not be universally considered subfields of mathematics proper.

Statistics, for example, is mathematical in its methods but grew out of bureaucratic and scientific observations, which merged with inverse probability and then grew through applications in some areas of physics, biometrics, and the social sciences to become its own separate, though closely allied, field. Theoretical astronomy, theoretical physics, theoretical and applied mechanics, continuum mechanics, mathematical chemistry, actuarial science, computer science, computational science, data science, operations research, quantitative biology, control theory, econometrics, geophysics and mathematical geosciences are likewise other fields often considered part of the mathematical sciences.

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Biometrics in the context of Galton Laboratory

The Galton Laboratory of National Eugenics was a laboratory established for the research of eugenics, later for the study of biometry and statistics, and eventually human genetics, based at University College London (UCL) in London, England. Reflective of his focus on quantitative analysis that led to statistical heredity and eugenics. In the early 1900s, biometricians such as Karl Pearson and Mendelians like William Bateson were inspired by his work. In 1904, he launched his eugenics campaign at the Sociological Society, founded by Patrick Geddes and others. This was a step towards making eugenics a national social scientific program. The laboratory existed in name until 2020.

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Biometrics in the context of Palm print

A palm print is an image acquired of the palm region of the hand. It can be either an online image (i.e. taken by a scanner or CCD) or offline image where the image is taken with ink and paper.

The palm itself consists of principal lines, wrinkles (secondary lines), and epidermal ridges. It differs to a fingerprint in that it also contains other information such as texture, indents and marks which can be used when comparing one palm to another.

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Biometrics in the context of Hand geometry

Hand geometry is a biometric that identifies users from the shape of their hands. Hand geometry readers measure a user's palm and fingers along many dimensions including length, width, deviation, and angle and compare those measurements to measurements stored in a file.

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Biometrics in the context of 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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Biometrics in the context of Keystroke dynamics

Keystroke dynamics, keystroke biometrics, typing dynamics, or typing biometrics refer to the collection of biometric information generated by key-press-related events that occur when a user types on a keyboard. Use of patterns in key operation to identify operators predates modern computing, and has been proposed as an authentication alternative to passwords and PIN numbers.

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