A Seminar on

Fingerprint Recognitionin Biometrics

Presentation Outlines Biometrics Method of verification Why Fingerprint Recognition? Fingerprint Recognition Systems Fingerprint Sensors Fingerprint Verification and authentication Technologies used in fingerprint recognition Applications Advantages Limitations Present and Future of Fingerprint Recognition Conclusion

Biometrics

Biometrics is an advanced technology for superb security and authentication .The very term "biometric” it represent that "bio" means related to the biological study and "metric " means something, which is related to measurement. In network environment security is a crucial factor.

Method of Verification

There are two methods of verification for security.

Psychological Verification Verification of the organs of the human being,

which will have unique identification.There are five types of verifications. These are: Fingerprint. Handprint. Face measurement. Retinal scans. DNA analysis.

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Finger print

It involves the user placing his finger over a glass-plate, which resides over a high-resolution camera, which uses optical or electromagnetic means to take its snapshot.

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Handprint It compares a 3D image of the users hand to

that present in the system database. It is somewhat similar to finger print verification.

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Retinal scans. It involves imaging of the blood vessels in the

retina of the eye when infrared light of a certain frequency and wavelength is incident upon it. This energy is absorbed by the blood vessels is different in different individuals.

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Face measurement

Measuring this is as simple as taking a picture and analyzing the image from a security video capture. This technique enables the computer to use your face as your password and matching these to an existing database

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DNA analysis.

It involves in checking the DNA pattern of a human used when physical characteristics are unrecognizable

This is one Biometric that is judicially accepted. No human have identified similar DNA patterns except in twins.

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Behavioral Verification This involves in oral thing done by the individual.

There are 3 types of behavioral verifications, Typing Signature Voice

Typing Some systems measure things you do in addition to

the things you are, you will notice that your typing has a certain pattern. Some letters follow others in quick succession, while others take longer.

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Signature

Some qualities looked into include acceleration rates, direction, and pressure and stroke length. Here mainly concentrate on pressures. This pressures stored in back end for future significations.

Voice

It involves in the recognition of the voice of the individual.

Fingerprint Recognition

This is a technique used to match and identify unique finger prints that might need to be stored and then accessed in a database.

Why Fingerprint Recognition?

Pin's and passwords may be forgotten The fingerprints in twins are not the same. Relies on the concept that no two people have identical

fingerprints. More secure. A person's fingerprint will not naturally change structure

after about one year after birth

Fingerprint Recognition Systems

Fingerprint Recognition System is a free tool that will

recognize and verify fingerprints.

Fingerprint Identification System is

a biometric identification (ID) methodology that uses

digital imaging technology to obtain, store, and

analyze fingerprint data. 

The three main functions of fingerprint Recognition

Systems are:

1) Acquisition of fingerprints

2) Derivation of characteristics and

3) Matching

Fingerprint sensors

Fingerprint Scanners are security systems of Biometrics. They are now used in police stations, security industries and most recently, on computers.

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.

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There are two types of fingerprint scanners:

1. The optical scanner 

Optical fingerprint imaging involves capturing a digital image of the print using visible light.

2. The Ultrasonic Scanner

Ultrasonic sensors make use of the principles of medical ultra sonography in order to create visual images of the fingerprint.

Verification and Authentication

This refers to the automated method of verifying a match between two human fingerprints.

The analysis of fingerprints for matching purposes generally are of two types

1)PatternsThe three basic patterns of fingerprint ridges

They are: a) Arch b) Loop c) Whorl

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Arch: The ridges enter from one side of the finger, rise in the center forming an arc, and then exit the other side of the finger.

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Loop: The ridges enter from one side of a finger and then exit on that same side.

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Whorl: Ridges form circularly around a central point on the finger.

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2)Minutia

The major Minutia features of fingerprint ridges are

a) Ridge ending

b) Bifurcation.

c) Short Ridge (Dot).

a) Ridge ending

The ridge ending is the point at which a ridge terminates

Ridge ending.

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. Bifurcation

Bifurcations are points at which a single ridge

splits into two ridges.

Bifurcation.

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Short ridges

Short ridges (or dots) are ridges which are significantly shorter than the average ridge length on the fingerprint.

Short Ridge (Dot).

Techniques used in Fingerprint

The techniques used in fingerprint recognition are:

a. Phase based image matching

b. Minutia score matching

Phase based image matching

Pattern based algorithms compare the basic fingerprint patterns (arch, whorl, and loop) between a previously stored template and a candidate fingerprint

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In a pattern-based algorithm, the template contains the type, size, and orientation of patterns within the aligned fingerprint image.

The candidate fingerprint image is graphically compared with the template to determine the degree to which they match

The proposed algorithm consists of the four steps

(i) core detection,

(ii) rotation and displacement alignment,

(iii) common region extraction and

(iv) fingerprint matching.

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(i) core detection,

The core is defined as a singular point in a fingerprint image that exhibits the maximum ridge line curvature

(ii) rotation and displacement alignment

We need to normalize the displacement and the rotation between the registered fingerprint and the input fingerprint in order to perform the high-accuracy fingerprint matching

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(iii) Common region extraction Next step is to extract the overlapped region

(intersection) of the two images we examine the n1-axis projection and the n2-axis projection of pixel values. Only the common effective image areas, with the same size are extracted

(iv) Fingerprint matching We calculate the BLPOC function between the

two extracted images and, and evaluate the matching score. The BLPOC function may give multiple correlation peaks due to elastic fingerprint deformation. Thus, we define the matching score between the two images as the sum of the highest two peaks of the BLPOC function.

Minute score matching

A good quality fingerprint contains 25 to 80 minutiae depending on sensor resolution and finger placement on the sensor.

The false minutiae are the false ridge breaks due to insufficient amount of ink and cross-connections due to over inking.

It is difficult to extract reliably minutia from poor quality fingerprint impressions arising from very dry fingers and fingers mutilated by scars, scratches due to accidents, injuries.

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Minutia based fingerprint recognition consists of Thinning, Minutiae extraction, Minutiae matching and Computing matching score.

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Binarization: Binarization converts gray scale image into binary image by fixing the threshold value. The pixel values above and below the threshold are set to ‘1’ and ‘0’ respectively.

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Block Filter:

The binarized image is thinned using Block Filter to reduce the thickness of all ridge lines to a single pixel width to extract minutiae points effectively.

Dilation and erosion are used to thin the ridges.

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Minutiae Extraction

The minutiae location and the minutiae angles are derived after minutiae extraction.

The terminations which lie at the outer boundaries are not considered as minutiae points, and Crossing Number is used to locate the minutiae points in fingerprint image.

Crossing Number is defined as half of the sum of differences between intensity values of two adjacent pixels.

If crossing Number is 1, 2 and 3 or greater than 3 then minutiae points are classified as Termination, Normal ridge and Bifurcation respectively

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Minutiae Matching

To compare the input fingerprint data with the template data Minutiae matching is used.

For efficient matching process, the extracted data is stored in the matrix format.

The data matrix is as follows.

Number of rows: Number of minutiae points. Number of columns: 4 Column 1: Row index of each minutia point. Column 2: Column index of each minutia point. Column 3: Orientation angle of each minutia point. Column 4: Type of minutia. (A value of ‘1’ is assigned

for termination, and ‘3’ is assigned for bifurcation).

Applications

Fingerprint based biometrics has primarily been used to secure entry devices for building door locks and computer network access.

A small number of banks use fingerprint readers for authorization at ATMs.

Grocery stores are experimenting with a fingerprint scan checkout that automatically recognizes and bills a registered user’s credit card or debit account.

More recent applications of finger recognition include use of fingerprints for voter registration.

Advantages It provide good security mechanism than all other

security methods It never fails in security constraints. In public locations such as banks and airports a large

number of people transit every day including known criminals. Face recognition systems attached to video surveillance systems are supposed to help catch them.

Fairly small storage space is required for the biometric template, reducing the size of the database required.

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It is one of the most developed biometrics, with more history, research, and design.

Each and every fingerprint including all the figures are unique, even identical twins have different finger prints.

Sound potential for enrich use as most of the countries have existing fingerprint databases.

Relatively inexpensive and offers high levels of accuracy

Limitations

It needs high memory space in the back end. Collect data for security is difficult Some times fails the security with right users Any time data loose in database high effect for

security mechanism. So many equipments are needed for provide this

technology. It highly expensive

Present and Future of Fingerprint Recognition

Today, fingerprint recognition technology is used for security purposes, to restrict assess or to protect computers. 

As fingerprint recognition technology develops, it is expected that more affordable and more portable fingerprint recognition devices will become available, and finger-print recognition will be considered a safe and convenient personal identification system.

Eventually, fingerprint recognition will be used to secure the safety and reliability of a variety of businesses in the industrial sector, including the personal devices and financial industry.

Conclusion

Security is not just about putting big locks on the front door; it also involves making sure all the windows are shut. Each one can be individually fooled, but the comparison makes the system more secure as a whole. Biometrics are have its own advantages and disadvantages. It high expensive but it provide good security. Money is not important than security. It is more useful for confidential maters.