Finger Print Biometric scan - Biometric Technology

Biometric Technology

Biometrics comprises methods for uniquely recognising humans based upon one or more intrinsic physical or behavioural traits. In information technology, in particular, biometrics is used as a form of identity access management and access control. Biometric Technology is also used to identify individuals in groups that are under surveillance.

Biometric characteristics can be divided in two main classes:

  • Physiological are related to the shape of the body. Examples include, fingerprint, face recognition, DNA, hand and palm geometry, iris recognition etc.
  • Behavioral are related to the behaviour of a person. Examples include, typing rhythm, gait and voice. Some researchers have coined the term behaviometrics for this class of biometrics. Strictly speaking, voice is also a physiological trait because every person has a different vocal tract, but voice recognition is mainly based on the study of the way a person speaks, commonly classified as behavioral.

Some of the Commonly used Biometrics:

Fingerprints – A fingerprint includes patterns found on a fingertip. There are a variety of approaches to fingerprint verification, such as traditional police method and using pattern-matching devices. Fingerprint scanning seems to be a good choice for in-house systems.

Finger Print Biometric scan - Biometric Technology

Hand geometry – This involves analyzing and measuring the shape of the hand. It might be suitable where there are more users or where user access the system infrequently. Accuracy can be very high if desired, and flexible performance tuning and configuration can accommodate a wide range of applications. Organizations are using hand geometry readerss in various scenarios, including time and attendance recording.

Retina – A retina-based biometric involves analyzing the layer of blood vessels situated at the back of the eye. This technique involves using a low intensity light source through an optical coupler to scan the unique patterns of the retina. Retinal scanning can be quite accurate but does require the user to look into a receptacle and focus on a given point.

Iris – An iris-based biometric involves analyzing features found in the coloured ring of tissue that surrounds the pupil. This uses a fairly conventional camera element and requires no close contact between the user and the reader. Further, it has the potential for higher than average template-matching performance.

Face – Face recognition analyses facial characteristics. It requires a digital camera to develop a facial image of the user for authentication. Because facial scanning needs an extra peripheral things that are not included in basic PCs, it is more of a niche market for network authentication.

Signature – Signature verification analyses the way user signs his name. Signing features such as speed, velocity, and pressure are as important as the finished signature’s static shape. People are used to signatures as a means of transaction-related identity verification.

Voice – Voice authentication is based on voice-to-print authentication, where complex technology transforms voice into text. Voice biometrics requires a microphone, which is available with PCs o within headphones nowadays. Voice biometrics is to replace the currently used methods, such as PINs, passwords, or account names. But voice will be a complementary technique for finger-scan technology as many people see finger scanning as a higher authentication form.

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