Over the last few years a new area of engineering science has been established whose products are likely to create a large market in the near future. It has been called ''biometrics". The pioneers of this new domain intend to construct devices which would allow identification of a person on the basis of his/her ''biological'' characteristics: voice, dynamics of movements, features of face and other parts of the body, retina or iris pattern.
The paper gives an overview of fingerprint technology in biometrics. Fingerprint identification by using artificial neural network with optical wavelet preprocessing is discussed. The various opportunities for biometrics is mentioned, followed by the uses, benefits, drawbacks, and applications of fingerprint processing.
WHAT TO LOOK FOR WHEN CHOOSING A
BIOMETRIC SECURITY SOLUTION
HISTORY OF FINGERPRINT
FINGERPRINT IMAGE ENHANCEMENT
FINGERPRINT IDENTIFICATION BY USING
ARTIFICIAL NEURAL NETWORK WITH
OPTICAL WAVELET PREPROCESSING
THE NEW OPPORTUNITIES FOR
Over the last few years a new area of engineering science has been established whose products are likely to create a large market in the near future. It has been called ''biometrics". The pioneers of this new domain intend to construct devices which would allow identification of a person on the basis of his/her ''biological'' characteristics: voice, dynamics of movements, features of face and other parts of the body, retina or iris pattern. However, the greatest hope seems to be lying in the possibility of the fingertip structure recognition (this structure is reflected in the fingerprint pattern). It is well known that the finger ridge pattern is different for each individual and that it does not change over the life time. Touching of a sensor surface is a simple act. Many inventors of biometric devices hope to develop a button which would ''know'' by whom it has been pressed and which finger has been used. A button used for the door unlocking would of course let in only authorized people and this is what the whole new area wants to live of.
Biometrics refers to the automatic identification of a person based on his/her physiological or behavioral characteristics. This method of identification is preferred over current methods involving passwords and PIN numbers for various reasons: the person to be identified is required to be physically present at the point-of-identification; identification based on biometric techniques obviates the need to remember a password or carry a token. With the increased use of computers as vehicles of information technology, it is necessary to restrict access to sensitive/personal data. By replacing PINs, biometric techniques can potentially prevent unauthorized access to or fraudulent use of ATMs, cellular phones, smart cards, desktop PCs, workstations, and computer networks. PINs and passwords may be forgotten, and token based methods of identification like passports and driver's licenses may be forged, stolen, or lost. Thus biometric systems of identification are enjoying a renewed interest.
There are two different ways to resolve a person's identity: verification and identification. Verification (Am I whom I claim I am) involves confirming or denying a person's claimed identity. In identification, one has to establish a person's identity (Who am I). Each one of these approaches has it's own complexities and could probably be solved best by a certain biometric system.
What to look for when choosing a biometric security solution:
There are many factors to look at when evaluating biometric technologies like:
Â¢ Does the technique rely on a truly unique characteristic and what is the scientific basic for that characteristic's uniqueness
Â¢ Can the process perform real-time exhaustive search in any size database
Â¢ How employees/customers will respond to the new technology
Â¢ Cost of equipment/software (cost per user)
Â¢ Implementation costs
Â¢ Maintenance costs
Â¢ Can the equipment be used for other uses
History of Fingerprint Identification:
In 1864, English plant morphologist, Nehemiah Grew, published the first scientific paper reporting his systematic study on the ridge, furrow, and pore structure in fingerprints. Since then, a large number of researchers have invested huge amount of effort on fingerprint studies. Recently, due to the raising demand in our increasing electronically inter-connected society for automatic personal identification and the success of various AFIS installations in forensics, automatic fingerprint identification technology has rapidly grown beyond forensic applications into civilian applications. In fact, fingerprint based biometric systems are so popular that they have almost become the synonym of biometric systems.
Fingerprint Scanning: Fingerprint scanning is the acquisition and recognition of a personâ„¢s fingerprint characteristics for identification purposes. This allows the recognition of a person through quantifiable physiological characteristics that verify the identity of an individual. There are basically two different types of finger-scanning technology that make this possible. One is an optical method, which starts with a visual image of a finger. The other uses a semiconductor-generated electric field to image a finger.
Practical Applications for Fingerprint Scanning: Fingerprint scanning has a high accuracy rate when users are sufficiently educated. Fingerprint authentication is a good choice for in-house systems where enough training can be provided to users and where the device is operated in a controlled environment. The small size of the fingerprint scanner, ease of integration - can be easily adapted to keyboards, and most significantly the relatively low costs make it an affordable, simple choice for workplace access security.
Fingerprint Identification: Among all the biometric techniques, fingerprint-based identification is the oldest method which has been successfully used in numerous applications. Everyone is known to have unique, immutable fingerprints. 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. Minutiae points are local ridge characteristics that occur at either a ridge bifurcation or a ridge ending.
Fingerprint Matching: Fingerprint matching techniques can be placed into two categories: minutiae-based and correlation based. Minutiae-based techniques first find minutiae points and then map their relative placement on the finger. 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. Also this method does not take into account the global pattern of ridges and furrows. However, it has some of its own shortcomings. Correlation-based techniques require the precise location of a registration point and are affected by image translation and rotation.
Fingerprint Classification: Fingerprint classification is a technique to assign a fingerprint into one of the several pre-specified types already established in the literature which can provide an indexing mechanism. Fingerprint classification can be viewed as 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.
Fingerprint Image Enhancement: 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. In order to ensure that the performance of an automatic fingerprint identification/verification system will be robust with respect to the quality of the fingerprint images, it is essential to incorporate a fingerprint enhancement algorithm in the minutiae extraction module.
Fingerprint identification by using artificial neural network with optical wavelet preprocessing:
The advantages of optical wavelet transform used as a preprocessor for an artificial neural network are investigated. It is shown by digital simulation that this set-up can successfully identify and discriminate complex biometric images, such as fingerprints. The achieved capabilities include limited shift-, rotation-, scale- and intensity-invariance. It is also shown that the edges-enhancement filter, applied before the wavelet transform, significantly improves abilities of the system.
Fingerprint identification by using artificial neural network with optical wavelet preprocessing
Fig. 1. Flow chart of the recognition system.
Fig. 2. Electronic ANN module with Optical Wavelet Preprocessor based on VanderLugt correlator.
The recognition is performed by the artificial neural network with built-in position invariance. Proper choice of the learning method additionally provides rotation-, scale-, and intensity-invariance. To some extent also occluded images can be properly identified.
The New Opportunities for Biometrics:
Since September 11, interest in biometrics technology has dramatically increased, creating a rush of opportunities for VARs and integrators. After decades of Orwellian notions and skepticism surrounding devices that identify individuals by personal characteristics such as their fingerprint, face, or voice, biometric products have finally come of age. No longer has a fad or science fiction gadget, biometric technology matured to become a real solution for preventing unwanted access. With biometric deployments on the rise, access control VARs and system integrators have an excellent opportunity to provide both new and existing customers complete biometric solutions.
Sample devices for fingerprinting biometrics:
Uses for Biometric technology:
Â¢ ATM, kiosk, and ticketing machines that recognize an authorized valid user (with or without card or PIN)
Â¢ Integrated personal identifiers for credit card verification at point-of-sale or identification of a customer without a credit card
Â¢ Stationary and mobile platforms for licensing, registration, and border security programs
Â¢ Travel security systems with passport, ticket, and baggage verification
Â¢ Business, residence, and vehicle security with access and operator authentication
Â¢ Processing and circulation control in the corrections (prison) environment, and
Â¢ Portable systems for on-scene recognition of individuals for police and military use
o Since fingers experience so much wear and tear from cuts and burns, software must be able to do image rebuilding. This capability is important for a biometric device to be reliable in real-life conditions.
o Can be perceived as an invasion of privacy. People may fear a "big brother" scenario if they use fingerprints for identification.
Biometrics is a rapidly evolving technology which is being widely used in forensics such as criminal identification and prison security, and has the potential to be used in a large range of civilian application areas. Biometrics can be used to prevent unauthorized access to ATMs, cellular phones, smart cards, desktop PCs, workstations, and computer networks. It can be used during transactions conducted via telephone and internet (electronic commerce and electronic banking). In automobiles, biometrics can replace keys with key-less entry devices.
Current electronic security systems, which rely primarily on passwords, personal identification numbers, and authentication tokens (smart cards) to ensure that a client is an authorized user of a system, all have a common vulnerability,: the verification can be lost, stolen, duplicated, or guessed. With the use of biometric technology, this vulnerability can be nearly eliminated.
Different organizations place different value on information protection. Pharmaceutical companies and technology companies will get great lengths to protect against security threats to protect their data and patents. These types of companies may wish to use biometrics to increase security levels.
While to possibilities for biometrics are great, biometric technology may not be the answer for everyone. The costs per user for some solutions may still be too high. Also to be considered, are the legal considerations of using biometrics, specifically privacy issues. However, for some, biometrics may be the answer.
please read http://www.seminarprojects.org/t-biometr...t-and-iris
for getting more information of Biometrics and Fingerprint related information