28-12-2012, 12:53 PM
Finger Print Recognition System
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INTRODUCTION
Fingerprint being the oldest and easily available trait of biometrics, offers an infallible means of personal identification. The matching accuracy using fingerprint has been shown to be very high as compared to other existing biometric traits. Unlike face and voice patterns, fingerprints are persistent with age and can’t be easily distinguished. Therefore, fingerprint is one of the most researched and matured field of biometric authentication. The first known example of biometrics in practice was a form of fingerprinting being used in China. Fingerprints are incomparably the most sure and unchanging form of all other forms of signature. A fingerprint is constituted by a set of ridge lines which often run parallel, sometimes terminates and sometimes intersects. The points where the ridge lines terminate or fork are called Minutiae whereas according to Galton, each ridge is characterized by numerous minute peculiarities called Minutiae, which may divide and almost immediately reunite, enclosing a small circular or elliptical space or sometimes the independent beginning or ending of ridges. In a fingerprint image, ridges are dark whereas valleys are bright. Ridges and valleys often run in parallel; sometimes they bifurcate and sometimes they terminate. Minutiae based fingerprint identification system approaches towards extraction of the ridge patterns correctly.
A good quality fingerprint contains 25-80 numbers of minutiae depending on the sensor resolution and finger placement on the sensor. However the fingerprint image captured through poor scanners, are found to have fewer number of minutiae points.
In order to ensure the minutiae extraction procedure to be healthy one, the system must have good quality of fingerprint images as input, and this gives a reason to the fingerprint images for enhancement.
Fingerprint Sensors
A fingerprint sensor is an electronic device used to capture a digital image of the fingerprint pattern. The captured image is called a live scan. This live scan is digitally processed to create a biometric template (a collection of extracted features) which is stored and used for matching. This is an overview of some of the more commonly used fingerprint sensor technologies.
Optical
Optical fingerprint imaging involves capturing a digital image of the print using visible light. This type of sensor is, in essence, a specialized digital camera. The top layer of the sensor, where the finger is placed, is known as the touch surface. Beneath this layer is a light-emitting phosphor layer which illuminates the surface of the finger. The light reflected from the finger passes through the phosphor layer to an array of solid state pixels (a charge-coupled device) which captures a visual image of the fingerprint. A scratched or dirty touch surface can cause a bad image of the fingerprint. A disadvantage of this type of sensor is the fact that the imaging capabilities are affected by the quality of skin on the finger. For instance, a dirty or marked finger is difficult to image properly. Also, it is possible for an individual to erode the outer layer of skin on the fingertips to the point where the fingerprint is no longer visible. It can also be easily fooled by an image of a fingerprint if not coupled with a "live finger" detector. However, unlike capacitive sensors, this sensor technology is not susceptible to electrostatic discharge damage.
Ultrasonic
Ultrasonic sensors make use of the principles of medical ultrasonography in order to create visual images of the fingerprint. Unlike optical imaging, ultrasonic sensors use very high frequency sound waves to penetrate the epidermal layer of skin. The sound waves are generated using piezoelectric transducers and reflected energy is also measured using piezoelectric materials. Since the dermal skin layer exhibits the same characteristic pattern of the fingerprint, the reflected wave measurements can be used to form an image of the fingerprint. This eliminates the need for clean, undamaged epidermal skin and a clean sensing surface.
Capacitance
Capacitance sensors utilize the principles associated with capacitance in order to form fingerprint images. In this method of imaging, the sensor array pixels each act as one plate of a parallel-plate capacitor, the dermal layer (which is electrically conductive) acts as the other plate, and the non-conductive epidermal layer acts as a dielectric.
PATTERN RECOGNITION AND FEATURE EXTRACTION
A pattern is an arrangement of descriptors. It is characterized by the order of the elements of which it is made, rather than by the intrinsic nature of these elements. Pattern recognition is divided into two principle areas: Decision theoretic and Structural. Decision theoretic deals with patterns described using quantitative descriptors, such as length, area, and texture. Structural category deals with patterns best described by qualitative descriptors, such as the relational descriptors. A pattern class is a family of patterns that share some common properties. Pattern classes are denoted by w1, w2……ww, where W is the number of classes. Pattern recognition by machine involves techniques for assigning patterns to their respective classes-automatically and with as little human intervention as possible. Three common pattern arrangements used in practice are vectors, strings and trees. Pattern vectors are represented in the following form:
x = [x1, x2………….xn]
Where each component, xi represents the ith descriptor and n is the total number of such descriptors associated with the pattern. The nature of the components of a pattern vector x depends on the approach used to describe the physical itself.
METHODOLOGY
It consists of three components to identify finger print image:
1. Image Generation
2. Image Enhancement
3. Matching of Fingerprint Image
CONCLUSION
For over a century, fingerprints have been one of the most highly used methods for human recognition; automated biometric systems have only been available in recent years. The determination and commitment of the fingerprint industry, government evaluation and needs, and organized standards bodies have led to the next generation of fingerprint recognition, which promises faster and higher quality acquisition devices to produce higher accuracy and more reliability. Because fingerprints have a generally broad acceptance with the general public, law enforcement, and the forensic science community, they will continue to be used with many government’s legacy systems and will be utilized in new systems for evolving applications that require a reliable biometric.