20-10-2012, 10:44 AM
Biometrics and the Detailed Study of the Finger Print Analysis Technique
Biometrics and the Detailed.doc (Size: 158 KB / Downloads: 23)
Abstract
This paper deals with biometrics which is the physical measurement of one or more physical characteristics of an individual so that that particular person is identified. It also elaborates on the procedures in the study of biometrics using the finger print authentication technique. The main objective of this paper is to show how this technique can be used to enhance the security as it allows us to differentiate the imposter from the real person.
INTRODUCTION
In recent years, biometrics has attracted much attention and its research has rapidly expanded since it has many potential applications in computer vision, automatic access control system and communication. Biometrics is the science and technology of measuring and analyzing biological data. It is an automated method of recognizing a person based on physiological or behavioral characteristics. The features measured are finger print, face, hand geometry, hand writing, iris, voice, blood vessels in the retina, coloration in the cornea of the eye and DNA from tissue samples. Finger print detection is the first and important step of automatic finger print recognition. Biometrics is the measurement of one or more characteristics of an individual so that they may be identified. The characteristics therefore should be unique for every individual. There are two ways this information can be used. It can identify the individual by comparing the sample with an entire database of samples It can verify another piece of information (such as a swipe card or a unique reference number typed at a keypad) by comparing the sample supplied with other samples in a database. For biometric data to be useful it must meet certain criteria. It must be easy to collect the data and compare it with the database, unchanging over time.
ALGORITM BASED ON FINGER PRINTING
Matching algorithms are used to compare previously stored templates of fingerprints against candidate fingerprints for authentication purposes. In order to do this either the original image must be directly compared with the candidate image or certain features must be compared.
Fingerprint Matching
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 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. The correlation-based method is able to overcome some of the difficulties of the minutiae-based approach. 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 matching based on minutiae has problems in matching different sized (unregistered) minutiae patterns. Local ridge structures cannot be completely characterized by minutiae. They are trying an alternate representation of fingerprints which will capture more local information and yield a fixed length code for the fingerprint. The matching will then hopefully become a relatively simple task of calculating the Euclidean distance will between the two codes.
FINFER PRINT CLASSIFICATION
Large volumes of fingerprints are collected and stored every day in a wide range of applications including forensics, access control, and driver license registration. An automatic recognition of people based on fingerprints requires that the input fingerprint be matched with a large number of fingerprints in a database (FBI database contains approximately 70 million fingerprints!). To reduce the search time and computational complexity, it is desirable to classify these fingerprints in an accurate and consistent manner so that the input fingerprint is required to be matched only with a subset of the fingerprints in the database. 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. There is an algorithm to classify fingerprints into five classes, namely, whorl, right loop, left loop, arch, and tented arch. The algorithm separates the number of ridges present in four directions (0 degree, 45 degree, 90 degree, and 135 degree) by filtering the central part of a fingerprint with a bank of Gabor filters. This information is quantized to generate a Finger Code which is used for classification.
CONCLUSION
Biometrics is one of the best methods of ensuring security. As the complexity increases, guarding every facet becomes difficult. Fingerprint recognition has helped eliminate the problem to a great extent. It is already being implemented in various fields. Government, IT companies, Banks, industries and many more places depend on fingerprint recognition system for their security. However there is always a scope for improvement .Sometimes fingerprints can be forged that is the security is not stringent enough. Adequate measures should be taken and more research needs to be done.