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fingerprint based car ignition system

A system to avoid car theft
by

usman moin

on 31 May 2011

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Transcript of fingerprint based car ignition system

Project title:

“Fingerprint Based Car Ignition System” Advisor: Dr. Nazar Abbas

Co-advisor: Nasir Mehmood


Group Members:

Usman Aziz (2006-NUST-BEE-159)

Saad Hussain (2007-NUST-BEE-290)

Usman Moin (2007-NUST-BEE-303) Abstract

Fingerprint based car ignition system is a system that is based on biometrics.

The system replaces the existing manual ignition system of a vehicle with the fingerprint recognition of the user.

The engine starts when the user puts his finger on the fingerprint sensor and has been verified.

The voice IC and LCD guides the user about the system . The System System Specifications

Enrollment and un-enrollment of different users

Enable system (ignition with fingerprint)

Disable system (ignition with key)

Empty the fingerprint library (Delete all users)



Note:
These specifications can be accessed only by entering the correct password from the keypad. List of Components

Fingerprint Module R303A
Voice IC ISD2590
Speaker
4x3 Keypad
16x2 LCD
12V Relays
Resistors (1k, 5k, 10k, 12k,)
Capacitors (1uF, 22uF, 33pf)
Transistors C1383
AVR ATMEGA 16
ATMEL 89c51 Fingerprint Module R303A Related Work and Literature Survey

Study of Microcontrollers
Study of Biometrics
Study of Fingerprint system
Study of the relevant data sheets of desired ICs
Study of desired components to use.


The tools to be used for this project are following:
AVR Studio
WinAVR
Orcad
Proteus What is Biometrics?

A technology of using human body characteristics such as fingerprints, eye retinas and irises, voice patterns, facial patterns and hand measurement for authentication purposes. Biometric Authentication System

Constitutes three basic processes:
User enrollment
Storage of biometric samples
User authentication Categories of Biometrics

Physiological biometrics which is related to the shape of the body.
Examples include: DNA, ear, face, fingerprint, hand geometry, iris and retina


Behavioral biometrics which is related to the behavior of a person.
Examples include: gait, signature and voice Applications of Biometrics

Categorized into five main groups:


1.Forensic applications
e.g. Identification of criminals, Surveillance, Corrections, Probation.


2.Government applications
e.g. National Identification Cards, Voter ID and Elections, Employee authentication, Military programs.

3.Commercial applications
e.g. Account access, ATMs, Online banking, Telephony transaction, E-commerce, Time and attendance monitoring.


4.Health Care applications
e.g. Access to personal information, Patient identification, medical informatics.


5.Travel and Immigration applications
e.g. Air travel, Border crossing, Employee access, Passports. Fingerprint System

A fingerprint

is an impression left by the friction ridges of a human finger



Friction ridge
a raised portion of the skin on the fingers. Fingerprint Identification

The process of comparing two instances of friction ridge skin impressions from human fingers, the palm of the hand or toes, to determine whether these impressions could have come from the same individual. Fingerprint Types

Exemplar prints
Fingerprints collected intentionally for some purpose.

Latent prints
Any by chance or accidental impression left by friction ridge skin on a surface.

Patent prints
The chance friction ridge impressions left on a surface by materials such as ink, dirt, or blood.

Plastic prints
A friction ridge impression left in a material that retains the shape of the ridge detail. e.g.candle wax, thick grease deposits on car parts, etc. Factors causing a fingerprint to appear differently from any known recording of the same friction ridges

flexibility of the skin

deposition pressure

slippage

the material from which the surface is made

the roughness of the surface

the substance deposited Fingerprint Sensors, Capturing and Detection

Fingerprint sensor
an electronic device that captures a digital image of the fingerprint pattern called a live scan*.

This live scan is digitally processed to create a biometric template (a collection of extracted features) which is stored and used for matching.

Live scan devices measure the physical difference between ridges and valleys.


*Live Scan is a technique with which Friction ridges can be recorded digitally. How Fingerprint Scanner Works? Fingerprint Recognition

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


Fingerprint matching consists of the comparison of several features of the print pattern, which include:

Patterns, which are aggregate characteristics of ridges

Minutia points, which are unique features found within the patterns Patterns

Loop : a pattern where the ridges enter from one side of a finger, form a curve, and tend to exit from the same side they enter


Whorl : a pattern in which ridges form circularly around a central point on the finger


Arc : a pattern where 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. Minutia

Ridge ending
the point at which a ridge terminates



Bifurcation
points at which a single ridge splits into two ridges



Short ridge (or dot)
ridges which are significantly shorter than the average ridge length on the fingerprint Pattern-based (or image-based) Algorithm

compares the basic fingerprint patterns (arch, whorl, and loop) between a previously stored template and a candidate fingerprint

the algorithm finds a central point in the fingerprint image and centers on that

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 Computational Algorithms for Fingerprint Recognition

Learned template based minutiae extraction algorithm

Triplets of minutiae based fingerprint indexing algorithm

Genetic algorithm based fingerprint matching algorithm

Genetic programming based feature learning algorithm for fingerprint classification

Comparison of classification and indexing based approaches for identification

Fundamental fingerprint matching performance prediction analysis and its validation
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