Voice recognition
Voice recognition is a technology that allows a user to use his/her voice as an input device. Voice recognition may be used to dictate text into the computer or to give commands to the computer (such as opening application programs, pulling down menus or saving work).
Older voice recognition applications require each word to be separated by a distinct space. This allows the machine to determine where one word begins and the next stops. These kinds of voice recognition applications are still used to navigate the computer's system and operate applications such as web browsers or spreadsheets.
Newer voice recognition applications allow a user to dictate text fluently into the computer. These new applications can recognise speech at up to 160 words per minute. Applications that allow continuous speech are generally designed to recognise text and format it, rather then controlling the computer system itself.
Voice recognition uses a neural net to 'learn' to recognise your voice. As you speak, the voice recognition software remembers the way you say each word. This customisation allows voice recognition, even though everyone speaks with varying accents and inflection.
In addition to learning how you pronounce words, a voice recognition also uses grammatical context and frequency of use to predict the word you wish to input. These powerful statistical tools allow the software to cut down the massive language database before you even speak the next word.
While the accuracy of voice recognition has improved over the past few years some users still experience problems with accuracy either because of the way they speak or the nature of their voice.
Iris recognition
Iris scan biometrics employs the unique characteristics and features of the human iris in order to verify the identity of an individual. The iris is the area of the eye where the pigmented or coloured circle, usually brown or blue, rings the dark pupil of the eye.
The iris-scan process begins with a photograph. A specialised camera, typically very close to the subject, no more than 90 centimetres, uses an infrared imager to illuminate the eye and capture a very high-resolution photograph. This process takes only one to two seconds and provides the details of the iris that are mapped, recorded and stored for future matching/verification.
Eyeglasses and contact lenses present no problems to the quality of the image and the iris-scan systems test for a live eye by checking for the normal continuous fluctuation in pupil size.
The inner edge of the iris is located by an iris-scan algorithm which maps the iris' distinct patterns and characteristics. An algorithm is a series of directives that tell a biometric system how to interpret a specific problem. Algorithms have a number of steps and are used by the biometric system to determine if a biometric sample and record is a match.
Irises are composed before birth and, except in the event of an injury to the eyeball, remain unchanged throughout an individual's lifetime. Iris patterns are extremely complex, carry an astonishing amount of information and have over 200 unique spots. The fact that an individual's right and left eyes are different and that patterns are easy to capture, establishes iris-scan technology as one of the biometrics that is very resistant to false matching and fraud.
The false acceptance rate for iris recognition systems is 1 in 1,2 million, statistically better than the average fingerprint recognition system. The real benefit is in the false-rejection rate, a measure of authenticated users who are rejected. Fingerprint scanners have a 3% false-rejection rate, whereas iris scanning systems boast rates at the 0% level.
Iris-scan technology has been piloted in ATM environments in England, the US, Japan and Germany since as early as 1997. In these pilots the customer's iris data became the verification tool for access to the bank account, thereby eliminating the need for the customer to enter a PIN number or password. When the customer presented their eyeball to the ATM machine and the identity verification was positive, access was allowed to the bank account. These applications were very successful and eliminated the concern over forgotten or stolen passwords and received tremendously high customer approval ratings.
Airports have begun to use iris-scanning for such diverse functions as employee identification/verification for movement through secure areas and allowing registered frequent airline passengers a system that enables fast and easy identity verification in order to expedite their path through passport control.
Other applications include monitoring prison transfers and releases, as well as projects designed to authenticate on-line purchasing, online banking, online voting and online stock trading to name just a few. Iris-scan offers a high level of user security, privacy and general peace of mind for the consumer.
A highly accurate technology such as iris-scan has vast appeal because the inherent argument for any biometric is, of course, increased security.
Hand scanning
This biometric approach uses the geometric form of the hand for confirming an individual's identity. Because human hands are not unique, specific features must be combined to assure dynamic verification.
Some hand-scan devices measure just two fingers, others measure the entire hand. These features include characteristics such as finger curves, thickness and length; the height and width of the back of the hand; the distances between joints and overall bone structure.
It should be noted that although the bone structure and joints of a hand are relatively constant traits, other influences such as swelling or injury can disguise the basic structure of the hand. This could result in false matching and non-false matching, however the amount of acceptable distinctive matches can be adjusted for the level of security needed.
To register in a hand-scan system a hand is placed on a reader's covered flat surface. This placement is positioned by five guides or pins that correctly situate the hand for the cameras. A succession of cameras captures 3D pictures of the sides and back of the hand. The attainment of the hand-scan is a fast and simple process. The hand-scan device can process the 3D images in 5 seconds or less and the hand verification usually takes less than 1 second. The image capturing and verification software and hardware can easily be integrated within standalone units. Hand-scan applications that include a large number of access points and users can be centrally administered, eliminating the need for individuals to register on each device.
Applications for hand scanning
Internationally, many airports use hand-scan devices to permit frequent international travellers to by-pass waiting lines for various immigration and customs systems.
Employers use hand-scan for entry/exit, recording staff movement and time/attendance procedures. This can go a long way to eradicating the age old problem of buddy-clocking and other deceptive activities.
Combining biometric methods
Hand-scanning can be easily combined with other biometrics such as fingerprint identification. A system where fingerprints are used for infrequent identification and hand-scanning is used for frequent verification would create a two tiered structure. The hand-scan component used frequently allows identity verification or 1:1 (one to one) verification that ensures the user is who they claim they are. The fingerprint identification component used infrequently, confirms who the user is and accurately identifies the user in a 1:N (one to many) identification that is compared with numerous records.
Multimodal biometrics systems
A multimodal biometric system uses multiple applications to capture different types of biometrics. This allows the integration of two or more types of biometric recognition and verification systems in order to meet stringent performance requirements.
A multimodal system could be, for instance, a combination of fingerprint verification, face recognition, voice verification and smartcard or any other combination of biometrics. This enhanced structure takes advantage of the proficiency of each individual biometric and can be used to overcome some of the limitations of a single biometric.
A multimodal system can combine any number of independent biometrics and overcome some of the limitations presented by using just one biometric as your verification tool. For instance, it is estimated that 5% of the population does not have legible fingerprints, a voice could be altered by a cold and face recognition systems are susceptible to changes in ambient light and the pose of the subject. A multimodal system, which combines the conclusions made by a number of unrelated biometrics indicators, can overcome many of these restrictions.
Multimodals are generally much more vital to fraudulent technologies, because it is more difficult to forge multiple biometric characteristics than to forge a single biometric characteristic.
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