Design and development of dorsal hand vein recognition biometric system using image processing on...

DEPARTMENT OF TELECOMMUNICATION ENGINEERING Dr. AMBEDKAR INSTITUTE OF TECHNOLOGYNear Jnana Bharathi Campus, Bangalore – 560056

Project Phase- I, 7th Semester(TEP77), TCE.

Presentation On

“Design and Development of Dorsal Hand Vein Recognition Biometric System Using Image Processing on FPGA”

By:Raghavendra D C 1DA10TE038Nischitha B M 1DA10TE034Navya L R 1DA10TE033

Under the Guidance of: Dr. B. Sivakumar Prof. & Head, Dept. of T.C.E.

Dr. A.I.T.1April 12, 2023

Outline of Presentation Objective Introduction Existing System Proposed System Literature Survey Block Diagram Methodology Implementation Expected Outcomes Advantages Disadvantages Applications Conclusion & Discussion References

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Design and Development of Dorsal Hand Vein Recognition Biometric System Using Image

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Objective

With an increasing emphasis on security, automated personal identification using hand Vein biometric feature is becoming a very active topic in both research and practical applications.

The objective of this work is to present a biometric authentication system for high security physical access control based on dorsal hand vein pattern.

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Introduction

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Biometric is an automated method of recognizing an individual based on measurable biological (anatomical and physiological) and behavioural characteristics.

We need biometric system because, now we are living in a global society of increasingly desperate and dangerous people who cannot be trusted based on identification documents, identity thieves steal PIN (date of birth) to withdraw money from accounts.

Dorsal hand vein recognition system is the identification of the person by recognizing the vein pattern presented in the back of hand.


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Existing System Existing Biometrics system includes fingerprint,

face, iris, voice, signature and geometry.

Fingerprint recognition:.

Face recognition:

• Iris recognition:

Voice recognition:


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Proposed system

To over come the existing above mentioned biometric system demerit we are developing a vein recognition system.

Dorsal hand vein recognition works by scanning the veins inside of back of hand and creating a digital template that represents vein pattern. It has the following advantages

Live Body Identification

Internal Features

Non-contact

High Security


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Literature Survey


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The term “biometrics” is derived from the Greek words

“bio” (life) and “metrics” (to measure).

The first biometric identification system based on

vascular structure called “VeinCheck” was presented by

Mac Gregor and Welford in 1991 .

In 2000 research paper describing the use of vascular

patterns for recognition is published by Sang-Kyun and

Soo-Won Kim. This paper describes the technology that

was to become the first commercially available vascular

pattern recognition system in 2000. The technology uses

the subcutaneous blood vessel pattern in the back of the

hands to achieve recognition.

Block Diagram

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System Level Block Diagram:

It consists of following components:

Person Showing Hand Camera Spartan 3e FPGA LEDs


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Algorithmic Level Block Diagram:

Image Acquisition Pre-processing

Segmentation

Post processing Feature Extraction

Matching

It consists of following blocks:

Image Acquisition

Pre-processing

Segmentation

Post Processing

Features Extraction

Matching Design and Development of Dorsal Hand Vein Recognition Biometric System Using Image

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Methodology

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Base Paper: Dorsal Hand Vein Biometry by Independent

Component Analysis by V.H. Yadav Department of Electronics &

Telecommunication. International Journal on Computer Science

and Engineering (IJCSE). ISSN : 0975-3397 Vol. 4 No. 07 July 2012.

(Pg No: 1338-1344).

o In this study, they have used the BOSPHORUS hand vein

database which has been taken under a source of near infrared

radiation. For feature extraction they applied appearance

based method Independent Component Analysis (ICA) which

produces independent components. To control over the number

of independent component, pre-processed the data by PCA

before applying ICA, and gives good experimental results.

ICA is very complicated method to extract the features hence we

are using a different method to realise this system.


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Near Infrared Imaging has been used to capture the image

since this produces a more clear vein pattern than visible light.

First pre-processing the image using median filters for

smoothing and noise removal and histogram stretching for

contrast enhancement.

Next image segmentation is performed using a filters that

emphasizes the directional nature of vein along with local

thresholding.

The image is then post processed to remove noise, using

morphological operations and blob removal.

Afterwards the entire pattern is thinned to a 1-pixel thick

skeleton which is used as a feature for matching and

recognition.

Images are matched using a Modified Hausdorff Distance which

produces an average distance between two thinned vein

patterns.

A threshold is used to decide if two vein patterns are similar or

not.


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Image processing algorithms will be designed and developed for identification of the back of hand and vein pattern.

This will be implemented in MATLAB/SIMULINK.

Verilog implementation of the same will be performed and implementation of the same is done on FPGA.

Interfacing of coloured lights to FPGA.

The hardware will be using are

o 3Mpixel Web Camera (more details will be given after purchase).

o Spartan 3e FPGA (Digilent).

o LEDs.

Implementation


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The software will be using are

o MATLAB/SIMULINK -software model for testing.

o MODELSIM- Simulation tool for Verilog/VHDL.

o Xilinx System Generator- Interface camera to FPGA.


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Designing system has two modes of operation - training mode and authentication mode.

In training mode it will update the database of vein pattern of user.

In authentication mode it will access the database to identify the user.

If authorized person shows the dorsal hand then blue light will glow otherwise red light will glow.

Expected Outcomes


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The vein patterns are unique to each individual and apart

from size, the pattern does not change over time.

A contact free technology involving no physical contact with

the hardware.

Extremely difficult to steal/misuse as veins are not visible to

naked eye.

Non-contact models are more hygienic than all forms of

contact biometrics.

Someone might take a picture of authorised user and show it

to the camera but system will not accept.

Advantages


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If the person lost his hand then this recognition won’t work.

Disadvantages

Applications

Biowatches and Biokeys.

Intelligent door handles, door locks.

Computer Logins.

POS(Point Of Sale) Authentication.

Time Attendance Applications.

Physical Access Control.Design and Development of Dorsal Hand Vein Recognition Biometric System Using Image

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Conclusion & Discussion

We need biometric system because, now we are living in a

global society of increasingly desperate and dangerous people

who cannot be trusted based on identification documents,

identity thieves steal PIN (date of birth) to withdraw money from

accounts.

Hence in this work, we are developing dorsal hand vein

biometric system.

Dorsal hand vein biometric system uses the subcutaneous blood

vessel pattern in the back of the hands to achieve recognition.

The length of the main vein and the angle at the bifurcation

points were used as the key features for this system.

It offers higher security and reliable for identification. Also it is

more advantageous than other biometric system


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Now we are developing a prototype of dorsal hand vein

biometric recognition system in which it will detect is

authenticated user is showing his dorsal hand or not, by

glowing the blue or red LED.

Future enhancement can be done for dorsal hand vein

recognition to send message to the predefined number

whether “authorised(with predefined name or ID)” or

“unauthorised” person is entering into the company. By doing

this one can know who is entering into company.

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References


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[1]

[2]

[3]

[4]

“Dorsal Hand Vein Biometry by Independent Component Analysis”

by V.H. Yadav Department of Electronics & Telecommunication.

International Journal on Computer Science and Engineering (IJCSE).

ISSN : 0975-3397 Vol. 4 No. 07 July 2012. (Pg No: 1338-1344).

“An Efficient Hand Dorsal Vein Recognition Based on Neural

Networks” by TUTUMLU H Erdinc KOCER and Novruz ALLAHVERDIc,

Selcuk University, Bozkır Vocational High School, Turkey. Journal of

Selçuk University Natural and Applied Science Online ISSN: 2147-

3781. (Pg No:28-39).

“Biometric Authentication by Dorsal Hand Vein Pattern” by C.

Nandini. International Journal of Engineering and Technology

Volume 2 No. 5, May, 2012. ISSN: 2049-3444 © 2012 – IJET

Publications UK. (Pg No:-837-840).

http://www.biometricupdate.com/201211/history-of-biometrics.

http://www.biometricupdate.com/201211/history-of-biometrics

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THANK YOU…!


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