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Biometric Image Discrimination Technologies (Computational Intelligence and Its Applications Series)

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Personal identification and verification both play a critical role in our society.
Today, more and more business activities and work practices are computerized. Ecommerce
applications, such as e-banking, or security applications, such as building
access, demand fast, real-time and accurate personal identification. Traditional knowledge-
based or token-based personal identification or verification systems are tedious,
time-consuming, inefficient and expensive.

Knowledge-based approaches use “something that you know” (such as passwords
and personal identification numbers) for personal identification; token-based
approaches, on the other hand, use “something that you have” (such as passports or
credit cards) for the same purpose. Tokens (e.g., credit cards) are time-consuming and
expensive to replace. Passwords (e.g., for computer login and e-mail accounts) are hard
to remember. A company may spend $14 to $28 (U.S.) on handling a password reset, and
about 19% of help-desk calls are related to the password reset problem. This may
suggest that the traditional knowledge-based password protection is unsatisfactory.
Since these approaches are not based on any inherent attribute of an individual in the
identification process, they are unable to differentiate between an authorized person
and an impostor who fraudulently acquires the “token” or “knowledge” of the authorized
person. These shortcomings have led to biometrics identification or verification
systems becoming the focus of the research community in recent years.

Biometrics, which refers to automatic recognition of people based on their distinctive
anatomical (e.g., face, fingerprint, iris, etc.) and behavioral (e.g., online/off-line
signature, voice, gait, etc.) characteristics, is a hot topic nowadays, since there is a
growing need for secure transaction processing using reliable methods. Biometricsbased
authentication can overcome some of the limitations of the traditional automatic
personal identification technologies, but still, new algorithms and solutions are required.
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