Biometric Fingerprints

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Among all the biometric techniques, fingerprint-based identification is the oldest method which has been successfully used in numerous applications. A fingerprint is made of a series of ridges and furrows on the surface of the finger. The uniqueness of a fingerprint can be determined by the pattern of ridges and furrows as well as the minutiae points.

1. Description

2. Why

3. How

4. Future Trends

5. Related Links

Description

Finger skin is made of friction ridges, with pores (sweat glands). Friction ridges are created during fœtal live and only the general shape is genetically defined. Friction ridges remains the same all life long, only growing up to adult size. They reconstruct the same if not too severe injury. Everyone is known to have unique, immutable fingerprints.While the overall appearence of monozygotic (identical) twins fingerprints is often similar, they differ in the fine details (the locations of ridge starting and stopping). In addition, they are no more similar to each other than to some prints of unrelated individuals.Fingerprint matching techniques can be placed into two categories:

  • Minutae Based
  • Correlation Based

Minutiae-based techniques first find minutiae points and then map their relative placement on the finger. Minutiae points are local ridge characteristics that occur at either a ridge bifurcation or a ridge ending.  However, there are some difficulties when using this approach. It is difficult to extract the minutiae points accurately when the fingerprint is of low quality.

Why

Biometric RFID system is more reliable compared to the existing RFID technology. This greatly avoids the misuse of Radio Frequency Identification Tags. Automated entry pints to highly restricted environments can use both theRFID and fingerprint authentication for authentication where as the other access points in the same environment can use RFID technology.By using Biometric RFID we avoid misuse of RFID tags and also enjoy using the contact less RFID authentication system at most of the access points. Since tags store datawith specific scaling, privacy is ensured for the users. This makes RFID technology a more reliable one to be used and extends usage of RFID technology at highly secured environments and for human tracking. The system overcomes the limitations of face recognition systems as well as fingerprint verification systems. The integrated prototype system operates in the identification mode with an admissible response time. The identity established by the system is more reliable than the identity established by a face recognition system.In addition, the decision fusion scheme enables performance improvement by integrating multiple cues with different confidence measures. It meets the response time as well as the accuracy requirements. 

How 

Fingerprint scanning secure entry devices for building door locks and computer network access are becoming more common. Recently a small number of banks have begun using fingerprint readers for authorization atATMs and grocery stores are experimenting with a fingerprint scan checkout that automatically recognizes and bills a registered user's credit card or debit account. The potential uses for this biometric appear to be limited only by the willingness of people to use it.Fingerprint classification is

  • An indexing mechanism to assign a fingerprint into one of the several pre-specified types already exist in the literature.

  • A coarse level matching of the fingerprints.

An input fingerprint is first matched at a coarse level to one of the pre-specified types and then, at a finer level, it is compared to the subset of the database containing that type of fingerprints only. A critical step in automatic fingerprint matching is to automatically and reliably extract minutiae from the input fingerprint images. However, the performance of a minutiae extraction algorithm relies heavily on the quality of the input fingerprint images.

  • The crossover accuracy of digital finger printing has been measured to be 1:500 for a single finger.

  • Use of multiple fingers increases the accuracy exponentially.

  • Because of the large amount of data that can be drawn from the fingerprints, as systems become more accurate and powerful.

  • Given the amount of information contained in a fingerprint, it is highly unlikely (estimated at 1 in 64 billion) that any two fingerprints would be identical and therefore impossible to tell apart.

Future Trends

A BioAPI compatible Architecture for mobile biometric fingerprint identification and verification, based on a XML Web Service and a Field Programmable Gate Array (FPGA). A Personal Digital Assistant (PDA) with a built-in fingerprint sensor and wireless LAN (WLAN) connectivity as a mobile client, and a Biometric Service Provider (BSP) running as a BioAPI compatible XML Web Service on the server side. BioAPI high level functions enrolment, identification and verification are implemented using BSP primitives, capture, process, createtemplate, verifymatch, and identifymatch that are partially hardware implemented using Handel-C and the Celoxica RC1000-PP platform.

Keywords

Fingerprint Identification, Personal identification, biometric recognition, Fingerprint classification

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