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International Journal of Modern Trends in Engineering

and Research www.ijmter.com

e-ISSN No.:2349-9745, Date: 28-30 April, 2016

@IJMTER-2016, All rights Reserved

Prototype of Fingerprint Based Licencing System For Driving Shubham S Jain

1, Chinmay M Jain

2, Yatin R Kasliwal

3

1E&TC, SNJB’S KBJ college of Engineering, Chandwad,[email protected]

2E&TC, SNJB’S KBJ college of Engineering, Chandwad, [email protected] 3E&TC, SNJB’S KBJ college of Engineering, Chandwad, [email protected]

Abstract: To prevent non-licensees from driving and therefore causing accidents, a new system is

proposed. Fingerprint identification is most reliable and important method in human identification.

Fingerprint identification is one of the most popular and reliable personal biometric identification

methods. The proposed system consists of a smart card capable of storing the fingerprint of particular

person. The licence issued by a person has stored their fingerprint in the card. Vehicles such as cars,

bikes etc. should have a card reader capable of reading the particular license. The same vehicle should

have the facility of fingerprint reader device. A person, who wishes to drive the vehicle, should insert

the card (license) in the vehicle and then swipe his/her finger. If the finger print stored in the card and

fingerprint swiped in the device matches, he/she can proceed for ignition, otherwise ignition system in

particular vehicle will not work. Moreover, the seat belt detector verifies and then prompts the user to

wear the seat belt before driving. This provide the security of vehicles and also ensures safe driving by

preventing accidents.

Keywords- Fingerprint, fingerprint reader, License, Ignition system, Smart Card, safe driving.

I. INTRODUCTION

Unlicensed driving is a matter of concern for several reasons. It is possible that drivers who have not

undergone appropriate training and testing may be deficient in some aspect of the knowledge and

skills required to drive safely and efficiently. Also, drivers who are unauthorized may have less

incentive to comply with road traffic laws in that they would not be influenced by the rewards and

penalties set up under the licensing system. On this argument, drivers who do not hold a valid license

may disregard the threat of license sanctions or the benefits of reduced insurance premium due to not

having made a claim. There appears to be a general flexible in the system of checking the validity of

documents and their ownership – for example it is claimed to be straightforward for an unlicensed

driver to pass himself off as a friend (with a license) and later present the friend‟s documents at a

police station. According to a survey by the AA Foundation for Road Safety Research it has been

estimated that in Sweden approximately half of all drunken driving takes place with drivers who do

not have a valid driving license (Goldberg, 1997). Also in Sweden, unlicensed driving has been

estimated as the cause of 100 deaths and 2500 injuries per year at a cost of more than one billion US

dollars. In the USA, in 1995, more than 10,000 lives were lost in fatal accidents with unlicensed drunk

drivers (approximately a quarter of all road deaths in that year). The equivalent figure in Great Britain

would therefore be over 900 deaths if this rate prevailed. An in built system in an automobile which

prevents such cases has therefore become vital. This paper aims to introduce a hardware architecture

which detects the fingerprint as well as the validity of the license of the driver and takes a robust

decision to turn on or off the ignition system based on the validity.

International Journal of Modern Trends in Engineering and Research (IJMTER)

Volume 3, Issue 4, [April 2016] Special Issue of ICRTET’2016

@IJMTER-2016, All rights Reserved 729

II. BLOCK DIAGRAM

Figure1.Block diagram of system

2.1. Smart card:

The license issued by the Government is a smart card which stores different fields such as name,

license no., date of expiry, fingerprints of 10 fingers, type of license and blocked status of the license

as well as fingerprint templates. The biometric fingerprint sensor will sense the digital picture of a

fingerprint. The fingerprint scan detects the ridges and valleys of a fingerprint and converts them into

ones and zeroes. Complex algorithms analyse this raw biometric scan to identify characteristics of the

fingerprint, known as the "minutiae". Minutiae are stored in a fingerprint template. Up to 200 minutiae

are stored in a template, but only a subset of these has to match for identification or verification. In

most systems, if 10 to 20 minutiae match, the fingerprint is considered a match. In today's smart card

systems approximately 40 minutiae are stored, because of space restrictions. This template is stored in

the smart card.

2.2. Fingerprint:

A finger prints are the most important part of human finger. It is experienced from the research that all

have their different finger prints and these finger prints are permanent for whole life. So fingerprints

have been used for the forensic application and identification for a long time. These finger print shows

the unique identification of a person. A fingerprint is the composition of many ridges and furrows.

Finger prints can‟t distinguished by their ridges and furrows. It can be distinguished by Minutia,

which are some abnormal points on the ridges. Minutia is divided in to two parts such as: termination

and bifurcation. Termination is also called ending and bifurcation is also called branch. Again minutia

consists of ridges and furrows. valley is also referred as furrow

2.3 Finger print recognition:

The fingerprint recognition problem can be grouped into two sub-domains such as:-

i) Fingerprint verification ii) fingerprint identification (Figure1.2.1).




Figure2. Fingerprint identification system

Fingerprint verification is the method where we compare a claimant fingerprint with an enrolee

fingerprint, where our aim is to match both the fingerprints. This method is mainly used to verify a

person‟s authenticity. For verification a person needs to his or her fingerprint in to the fingerprint

verification system. Then it is representation is saved in some compress format with the person‟s

identity and his or her name. Then it is applied to the fingerprint verification system so that the

person‟s identity can be easily verified. Fingerprint verification is also called, one-to-one matching.

Fingerprint identification is mainly used to specify any person‟s identity by his fingerprint.

Identification has been used for criminal fingerprint matching. Here the system matches the

fingerprint of unknown ownership against the other fingerprints present in the database to associate a

crime with identity. This process is also called, one-too many matching. Identification is traditionally

used for solve crime and catch thieves.

III. FINGERPRINT MATCHING ALGORITHM

Fingerprint identification is one of the most popular and reliable personal biometric identification

methods. This paper describes an on-line fingerprint identification system consisting of image

acquisition, edge detection, thinning, feature extractor and classifier. The pre-processing part includes

steps to acquire binaries and skeletonized ridges, which are needed for feature point extraction.

Feature points (minutia) such as endpoints, bifurcations, and core point are then extracted, followed

by false minutia elimination. Human fingerprints are rich in details called minutiae, which can be used

as identification marks for fingerprint verification. The algorithm that was implemented for finger

print matching in this research work is discussed below. Anil Jain et al proposed a hybrid matching

algorithm for matching. Our algorithm is described in detail below.

Step 1: Histogram Equalization:

Histogram equalization is to expand the pixel value distribution of an image so as to increase the

perception information. The original histogram of a fingerprint image has the bimodal type the

histogram after the histogram equalization occupies all the range from 0 to 255 and the visualization

effect is enhanced.

Step 2: Fourier Transform:




Because the image in the Fourier domain is decomposed into its sinusoidal components, it is easy to

examine or process certain frequencies of the image, thus influencing the geometric structure in the

spatial domain.

Step 3: Binarization:

A locally adaptive binarization method is performed to binarize the fingerprint image. Such a named

method comes from the mechanism of transforming a pixel value to 1 if the value is larger than the

mean intensity value of the current block (16x16) to which the pixel belong.

Step 4: Direction:

Field orientation and filtered field orientation map computation, which consists of the calculation of

the dominant direction of ridges and valleys in each local region.

Step 5: Region of Interest (ROI):

Two Morphological operations called „OPEN‟ and „CLOSE‟ are adopted. The „OPEN‟ operation can

expand images and remove peaks introduced by background noise. The „CLOSE‟ operation can shrink

images and eliminate small cavities.

Step 6: Thinning:

The built-in Morphological thinning function in MATLAB is used for ridge thinning. The thinned

ridge map is then filtered by other three Morphological operations to remove some H breaks, isolated

points and spikes.

Step 7: Matching:

A bounding box is placed around each template minutia. If the minutia to be matched is within the

rectangle box and the direction discrepancy between them is very small, then the two minutia pair is

regarded as a matched minutia pair. Each minutia in the template image either has no matched minutia

or has only one corresponding minutia. The number of matched minutia pair is calculated as

percentage of matching.

IV. IGNITION SYSTEM OF VEHICLE

The ignition system of an internal-combustion engine is an important part of the overall engine system

that provides for the timely burning of the fuel mixture within the engine. All conventional petrol

(gasoline) engines require an ignition system. The ignition system is usually switched on/off through a

Lock switch, operated with a key or code patch. The ignition system works in perfect concert with the

rest of the engine of a vehicle. The goal is to ignite the fuel at exactly the right time so that the

expanding gases can do the maximum amount of work that in line with the processes to make the

vehicle move. If the ignition system fires at the wrong time, power will fall and gas consumption and

emissions can increase. The part of the ignition system that first initiates the process of moving a

vehicle is the key system in conjunction with the kick starter. A wire from the battery in the vehicle

connects to the kick starter and other wires connect the kick starter to the key system. When the car

key in the ignition system is turned once, two wires coming from the kick starter to the key system are

bridged. This causes the engine and some other parts of the vehicle to be put in a READY or ON

state. Turning the key again makes a third wire to temporarily join the already bridged wires, causing

voltage to flow from the battery to the necessary parts vehicle so as to enable the vehicle move.

4.1. Controlling the Ignition System:

The mechanism of the ignition system comprises amongst other things, three wires that are connected

to the key system and used with the keys to ignite the vehicle. Two of these wires are bridged when

the key is turned first, causing current to flow from the car batteries to all parts of the car requiring

some form of electricity for operation. When the key is turned again, the third wire bridges

momentarily with the two wires already connected. This causes the cranking of the engine, which

ignites the vehicle. For the purpose of this research work, the three wires were disconnected from the




key system. The first two wires were connected to the first relay, and the third wire was connected to

the second relay. This was done to simulate the action of bridging two of the wires together when the

first relay is activated. Activating the second relay for a short time causes a temporary connection

between the two relays. This connects all three wires together, thus igniting the vehicle. The relays

were activated or deactivated by sending appropriate control signals from the fingerprint recognition

software, via the parallel port to the interface circuit. A correctly identified or verified image causes

the parallel port control codes in the fingerprint recognition software to send about 5volts to pin 2 of

the parallel port. This voltage passes on to the interface control circuit and subsequently activates the

first relay. After five seconds, about 5volts is sent again to the pin 3 of the parallel port for three

seconds. This activates the second relay for five 170 Omidiora E. O., Fakolujo O. A., Arulogun O. T.

and Aborisade D. O. seconds and deactivates it. The continuous activation of the first relay and the

momentary activation of the second relay cause the vehicle to be ignited. Conversely, an incorrectly

identified image causes the parallel port control codes in the fingerprint recognition software to send

about 0volts to pin 2 and pin 3 of the parallel port. Thus, no voltage passes on to the interface control

circuit and the two relays remain deactivated. This prevents the vehicle from being ignited.

V. CONCLUSION

From this we implement image-recognition techniques that can provide the important functions

required by advanced intelligent Car Security, to avoid vehicle theft and protect the usage of

unauthenticated users. Secured and safety environment system for automobile users and also key

points for the investigators can easily find out the hijackers image. We can predict the theft by using

this system in our day to day life. This will help to reduce the complexity and improve security.

REFERENCES

[1] Qijun Zhao, Lei Zhang, David Zhang, Nan Luo, “Adaptive Pore Model for Fingerprint Pore Extraction.” Proc.

IEEE, 978-1-4244-2175-6/08, 2008.

[2] Moheb R. Girgis, Tarek M. Mahmoud, and Tarek Abd-El- Hafeez, “An Approach to Image Extraction and

Accurate Skin Detection from Web Pages.” World academy of Science, Engineering and Technology, page no.

27, 2007.

[3] Manvjeet Kaur, Mukhwinder Singh, Akshay Girdhar, and Parvinder S. Sandhu, “Fingerprint Verification System

using Minutiae Extraction Technique.” World academy of Science, Engineering and Technology, page no. 46,

2008.

[4] Hoi Le, The Duy Bui, “Online fingerprint identification with a fast and distortion tolerant hashing.” Journal of

Information Assurance and Security 4 page no. 117-123, 2009.

[5] David Silcock, Anna Sunter & Chris van Lottum, Ross Silcock Limited, Kris Beuret, Social Research Associates,

“Unlicenced Driving: A Scoping Study to Identify Potential Areas for Further Research”Foundation for Road

Safety Research.

[6] Anil Jain, Yi Chen, and Meltem Demirkus, “Pores and Ridges: Fingerprint Matching Using Level 3 Features.”

Pattern recognition letters, page no. 2221-2224, 2004.

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