hand geometry biometric

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Agenda Background on biometrics Biometric categories Modes of operation Biometrics – how do they work Block diagram of biometric Characteristics comparison Hand geometry Advantages of hand geometry Disadvantages of hand geometry Applications of hand geometry Promise that biometric holds for privacy Future trends in biometrics Conclusion References 2

Background On Biometrics:

Background On Biometrics Biometrics First introduced in the 1970s and early 1980s This technology gathers unique physiological or behavioral attributes of a person for storing it in a database or comparing it with one already found in a database. Reason for biometrics include the positive authentication and verification of a person and ensuring confidentiality of information in storage 3

Biometrics Categories :

Biometrics Categories Behavioral – biometrics based on data derived from measurement of an action performed by a person . Physiological – also known as static biometrics based on data derived from the measurement of a part of a person’s anatomy. Retina scans Chemical composition of body Face DNA Fingerprints Hand geometry Handwritten signatures Voice patterns Gait 4

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: Modes Of Operation Verification – This system does a one to one comparison of a captured biometric with a stored template to verify the individual identity. Identification – This system does a one to many comparison of the captured biometric against a biometric database in attempt to identify an unknown individual. 5

Biometrics Devices – How Do They Work? :

Biometrics Devices – How Do They Work? A reader or scanning device Software that converts the scanned information into digital form and compares match points A database that stores the biometric data for comparison in an encrypted form; to prevent identity theft 6

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Any biometric device, consist of: Block Diagram Of Biometric System 7

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Biometric Universality Accuracy Stability User Acceptability Cost Circumvention Face H L M H L L Fingerprint M H H H L L Voice M L L H L L Iris H H H L H H Signature L L L H L L Gait M L L H L M Palm-print M H H M M M Characteristics Comparison 9

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HAND GEOMETRY Two or three dimensional hand image is taken using imaging technologies. Today these are usually CCD or CMOS imaging Characteristics typically recorded include length of fingers, curvature of fingers, thickness and width of fingers and palm, knuckle shape, distances between joints, hand surface area, bone structure .Approximately 90 measurements are taken and 31,000 points analysed in a full hand scan which ignores surface details such as scars, fingernails,fingerprints and dirt. Templates range from 9 to 20 bytes in size. Typical processing times involves: · Enrolment 30 to 60 seconds; · Scan 5 seconds; · Identification 1 to 10 seconds. 10

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Image Acquisition Phase During the enrollment phase, different hand images of the user are collected.and stored in separate files for matching. The user is asked to stretch his hand differently each time the image is acquired to avoid differences arising due to stretching of his hand. 11

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Feature Extraction Phase The colored image obtained from the scanner is processed before the features are extracted. Gray pixel G = 0.3RED + 0.59GREEN + 0.11BLUE. chain code contour extraction method 12

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The valley ends in between the fingers and tip ends at the top of the fingers serve as the landmark points for the extraction of features. The lengths and widths of the fingers are calculated using these end points. To obtain these end points, first the curves of the finger ends are extracted. 13

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Curve points (cp) of all the fingers are separated and are used to find the tip and valley ends Where a is the distance between the two offset points, b is the distance between the point p and the offset point before p c is the distance between p and offset point after p. For every point p on the hand contour, the angle made by the lines joining the p and offset points is calculated 14

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To obtain perpendicular distance from the curve points of the finger to the bisector is calculated by the given formula. Where (x1,y1) and (x2,y2) are the coordinates of the initial and final curve points. M is the slope between the offset points. Perpendicular distance D from the curve point c p (xcp,ycp) to the perpendicular bisector 15

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Once the tip and valley ends are obtained, various features of the hand are extracted from these points. 22 features have been considered for verification. As can be seen from the features the orientation of the hand does not effect the feature extraction. 16

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Verification Phase Each feature will be assigned a weight depending on the variance of the feature due to placement of the hand. For example the base width of a finger is assigned lower weight, since the width may change slightly (5%) when the user over-stretches his hand and also the length of the thumb changes when the user relaxes his hand during verification procedure. The heights of four fingers and the distance between the valley ends and tip ends remain constant in all circumstances, so they are assigned higher weights. The verification procedure involves assigning weights to the various features and matching with the pre-stored user’s feature templates 17

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Advantages Of Hand Geometry Ease of use- The technology is simple to use and has been in widespread use for many years. Small template size- The small template size allows fast processing, is important where large volumes of users are processed. The readers are durable and able to process large volumes of users of several years without undue reader failure. They can also withstand wide temperature ranges and operate in hostile (such as high temperature and dusty) environments. The technology has been in use for many years and has proved reliable. 18

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Disadvantages Of Hand Geometry Cost- Hand geometry scanners are relatively large and expensive Hand changes and injuries. While the basic structure of the hand changes little over time, injuries, swelling or diseases such as arthritis can obscure this structure and cause recognition difficulties· Accuracy -Hand geometry is not sufficiently distinctive to allow 1-to-many searches and is generally limited to 1-to-1 authentication uses. It’s use is therefore limited to identity verification rather than identification of an individual from a database. Hygiene concerns as multiple users touch the reader. 19

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Applications Of Hand Geometry hand geometry usage is attendance recording. A large number of US universities, colleges and day care centres use hand geometry scanning to control access to dormitories, classrooms, meal plans, libraries and so on. The U.S. Federal Bureau of Prisons uses hand geometry technology to monitor movements and control access for prisoners, staff and visitors Wells Fargo, Bank of America, Florida Credit Union and other US financial institutions have installed hand geometry readers for safety deposit box customers, allowing self-service and faster access without the need for a staff member to verify identity thorough a signature and then escort them to the deposit box storage area Walt Disney World has been using finger geometry scans to identify holders of annual and seasonal passes since 1996 20

Promise That Biometrics Hold For Privacy:

Promise That Biometrics Hold For Privacy Biometric cannot be lost, stolen or forgotten; it cannot be written down and stolen by social re-engineering By implementing biometrics organizations can positively verify users’ identities, improving personal accountability In conjunction with smart cards biometrics can provide strong security for Public Key Infrastructure (PKI) 21

Future Trends In Biometrics:

Future Trends In Biometrics Body Odor – Body odor can be digitally recorded for identification. A British company, Mastiff Electronic System Ltd. Is working on such a system. Thermograms – Thermograms requires an infrared camera to detect the heat patterns of parts of the body that are unique to every human being . Ear recognition – Suggestions have been made that the shapes and characteristics of the human ear are widely different from one another. 22


CONCLUSION All authentication methods are prone to errors. Nevertheless, reliable user authentication must ensure that an attacker cannot masquerade as a legitimate user Biometrics is uniquely bound to individuals and may offer organizations a stronger method of authentication Biometric systems are not foolproof. A prudent balance between Security and Privacy needs to be achieved 23

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REFERENCES Jain, A.K., Ross, A. and Pankanti, S., “A Prototype Hand Geometry-Based Verification System”, Proceedings of Second International Conference on Audio- and Video-based Biometric Person Authentication, Washingt on D.C., USA, pp. 166-171,1999. A.K. Jain, R. Bolle and S. Pankanti (Eds.), Biometrics: Personal Identification in Networked Society", Kluwer Academic Publishers, 1998. L. Wong and P. Shi, "Peg-Free Hand Geometry Recognition Using Hierarchical Geometry and Shape Matching", IAPR Workshop on Machine Vision Applications, Nara, Japan, December, 2002. Pp. 281-284. 24

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