BIO-METRICS
(Finger print image enhancement)

INTRODUCTION:

        Before we go any further let us define exactly what we mean when we talk about biometric technologies. The term 'biometrics' refers strictly speaking to a science involving the statistical analysis of biological characteristics. Here biometrics is used in a context of analysing human characteristics for security purposes. The distinction can be clarified with following definition:

"A biometric is a unique, measurable characteristic or trait of a human being for automatically recognizing or verifying identity."

      This measurable characteristic, Biometric , can be physical , such as eye, face, finger image, hand and voice or behavioural , like signature and typing rhythm. Biometric system must be able to recognize or verify it quickly and automatically.

      It is often said that with biometric products you are able to reach the highest level of security. To help illustrate this point, a much quoted

      "Biometrics” are automated methods of recognizing a person based on a physiological or behavioral characteristic.

      Examples of human traits used for biometric recognition include fingerprints, speech, face, retina, iris, handwritten signature, hand geometry, and wrist veins.

Biometric recognition:

      Biometric recognition can be used in identification mode, where the biometric system identifies a person from the entire enrolled population by searching a database for a match.

      A system also can be used in verification mode, where the biometric system authenticates a person's claimed identity from his/her previously enrolled pattern.

      Using biometrics for identifying and authenticating human beings offers some unique advantages. Only biometric authentication bases an identification on an intrinsic part of a human being. Tokens, such as smart cards, magnetic stripe cards, physical keys, and so forth, can be lost, stolen, duplicated, or left at home. Passwords can be forgotten, shared, or observed.

      While all biometric systems have their own advantages and disadvantages, there are some common characteristics needed to make a biometric system usable.

      First, the biometric must be based upon a distinguishable trait. For example, for nearly a century, law enforcement has used fingerprints to identify people. There is a great deal of scientific data supporting the idea that "no two fingerprints are alike."

      Newer methods, even those with a great deal of scientific support, such as DNA-based genetic matching, sometimes do not hold up in court.

       Most people find it acceptable to have their pictures taken by video cameras or to speak into a microphone. In the United States , using a fingerprint sensor does not seem to be much of a problem. In some other countries, however, there is strong cultural opposition to touching something that has been touched by many other people.

       While cost is always a concern, most implementers today are sophisticated enough to understand that it is not only the initial cost of the sensor or the matching software that is involved. Often, the life-cycle support cost of providing system administration support and an enrollment operator can overtake the initial cost of the hardware. Also of key importance is accuracy. Some terms that are used to describe the accuracy of biometric systems include false-acceptance rate (percentage of impostors accepted), false-rejection rate (percentage of authorized users rejected), and equal-error rate (when the decision threshold is adjusted so that the false- acceptance rate equals the false-rejection rate).
                                                        
      When discussing the accuracy of a biometric system, it is often beneficial to talk about the equal-error rate or at least to consider the false-

      acceptance rate and false-rejection rate together. For many systems, the threshold can be adjusted to ensure that virtually no impostors will be accepted. Unfortunately, this often means an unreasonably high number of authorized users will be rejected.

      To summarize, a good biometric system is one that is low cost, fast, accurate, and easy to use.

Facial recognition system:

      A facial recognition system is a computer driven application for automatically identifying a person from a digital image. It does that by comparing selected facial features in the live image and a facial database.

      It is typically used for security systems and can be compared to other biometrics such as fingerprint or eye iris recognition systems. The London Borough of Newham , in the UK , has a facial recognition system built into their borough-wide CCTV system; see also Closed-circuit television .

      Popular recognition algorithms include eigenface, fisherface and the Hidden Markov model.

      Critics of the technology complain that the LB Newham scheme has, as of 2004 , never recognised a single criminal, despite several criminals in the system's database living in the Borough and the system having been running for several years. An experiment by the local police department in Tampa , Florida , had similarly disappointing results.

 Physical anthropology:

      Physical anthropology , sometimes called "biological anthropology," studies the mechanisms of biological evolution, genetic inheritance, human adaptability and variation, primatology, and the fossil record of human evolution. See also: Race.

      Some of the early branches of physical anthropology, such as early anthropometry, are now rejected as pseudoscience. Metrics such as the cephalic index were used to derive behavioral characteristics.

Fingerprint recognition:

      Fingerprint recognition is a biometric security method that integrates with applications and other technologies to provide a way to identify a person by scanning a person's fingerprint to gain access.  Fingerprint recognition is a way to provide higher security because a fingerprint

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