Automatic Vehicle Number
Plate Recognition
Group Members
1. Roll No : 201614110, Capt Md. Mazharul Islam
2. Roll No : 201614124, Capt Mahadi Hassan Riad
Supervised By
Asst Prof Dr. T. M. Shahriar Sazzad
Outline & Overview
 Introduction
 Research Area
 Thesis Objective
 System Componenets
 Literature Review
 Methodology
 Results
 Discussion
 Conclusion
 References
 Questions & Answers
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1.
INTRODUCTION
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
Introduction
Traffic control and vehicle owner identification have become major problems in every
country like Bangladesh specially incase of important military installations where
security is the foremost priority.

In Bangladesh Armed Forces installations, in most of the MP Gates traditional rule is
followed for entry and exit of vehicles on the basis of lane separation for stickered
and non-stickered vehicles alongside of which Military police plays physical role for
ID confirmation of drivers.

This method is quite obsolete, risky incase of fraud entry, time consuming and
wastage of manpower which could be utilized in a more productive way to meet up
our present manpower crisis of Armed Forces. To suffice this situation we came up
with the idea of Automatic vehicle number plate recognition (AVNPR).
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Concept
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
In this system first an image of license plate is captured from a slowly moving vehicle
approaching towards MP gate by a powerful image capturing device(video camera) and
then the process of license plate detection method is performed using digital image
processing.
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After detecting the license plate, extracted plate number from image is compared with
already registered number plate in a database. In case of match it is allowed to cross MP
gate by automatic raising of barrier and only for mismatch, MP can play physical role for
ID confirmation.
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2.
RESEARCH
AREA
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Research Area
 Our main research area for this project is Digital Image
Processing(DIP) which mainly engulfs software part.
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3.
THESIS
OBJECTIVE
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Thesis Objective
The objective of our thesis are as follows:
 To analyze vehicle number plate using Digital
Image Processing to extract number plate no.
 To match the license plate no with the central
database system for internal verification of
registered and unregistered vehicles.
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4.
SYSTEM
COMPONENTS
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System Components

This project has two major components :
 Hardware component
 Software component

Software part consists of:



Matlab based Application
Database
Database contains all vehicles information whose license plate are already registered in
the system and information of admins in charge of several MP Gates.
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Hardware part comprises of following components:

Camera - that take close view images of the car number plate (front or rear side).
Camera should have following high end performances:
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System Components
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Weatherproof
High fps
Powerful IR
Powerful zooming lens
Computer - normally a PC running Windows. It runs the LPR application which
controls the system, reads the images, analyzes and identifies the plate, and
interfaces with other applications and systems.
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6.
LITERATURE
REVIEW
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Literature Review
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Ref
Num
Related Work
Limitations
[1]
Hao Chen England planned the method,
several candidates based on texture
information similar to license plate are
extracted and auto-correlation based
binary image and projection algorithm
are used to verify the true candidate
plate.
Time complexity as we
need to collect
samples from multiple
Image context to get
the best output for best
match.
2
Gisu Heo in Thailand developed license
plate detection technique using group of
lines forming rectangle at the plate
boundary, followed by this step is the
vertical edge density technique to find
out the plate area.
Not cost effective as
high end zooming lens
required for precise
edge detection for
vertical to horizontal
ratio.
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Literature Review
Index
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Related Work
Limitations
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Ozbay at Malaysia al developed
smearing algorithm to locate the license
plate
Not suitable for all sort
of vehicles as
Smearing algorithm
depends on the pixel of
the gap
between the characters
horizontally and
vertically which may
not work for compact
number plate.
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Mei Yu in Australia proposed vertical
edge detection followed by size, shape
filter for edge area and edge matching
technique based on plate model.
Not cost effective and
severe Memory
consumption rate even
though performance is
high.
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7.
METHODOLOGY
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METHODOLOGY
On the basis of literature review observed from existing system
We find following contradictions:

Time complexity

Space Complexity(Memory)

Universality

Cost Effectiveness

Suitability
So in order to balance these limitations we focus on a proposed
existing framework to get optimized system output which suits our
demanding environment.
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Flowchart of
Proposed framework
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7.
RESULT
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8.
Discussion
Discussion
Advantages:
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Faster mechanism for vehicle entry and exit which prevent long queue of vehicles.
Manpower savior by limiting number of MP operating due to system automation.
Better surveillance and security against any traffic occurrences inside cantonment
area as drivers ID enrolled.
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Trespassing reduced to a greater volume.
Limitations:
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Firstly, the images of the number plate or of any object which is taken by using the digital image processing
technology may get blurred mainly due to the reason of motion blurring .
In many cases due to any scratch on number plate or unwanted spot on video camera, system may
generate wrong number plate.
Due to COVID-19 situation we could not get the actual database information instead used dummy
database.
Any vehicle with registered number plate in database but different driver may cross MP gate unaware of
MP which is a loophole.
It is quite costly to set up LPR camera for every gate .
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9.
Conclusion
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Conclusion
Future Improvements:
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Provision for using double camera, one for plate & one for person identification so that
both match can only certify access of vehicle.
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Use of Actual Database and BRTA facilities and their suggestions for further improvement.
Identification and image processing of Bengali characters for universal purpose.
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References
1.
Hao Chen, Jisheng Ren, Huachun Tan, Jianqun
Wang, “ A novel method for license plate
localization”, 4th Proc. of ICIG 2007, pp. 604-609.
2.
Gisu Heo, Minwoo Kim, Insook Jung, Duk Ryong
Lee,Il Seok Oh, “Extraction of car license plate
regions using line grouping and edge density
methods”, International Symposium on Information
Technology Convergence, 2007, pp. 37-42.
3.
Serkan Ozbay, Ergun Ercelebi, “Automatic vehicle
identification by plate recognition”, Proc. of
PWASET, vol. 9, no. 4, 2005, pp. 222-225.
4.
Mei Yu and Yong Deak Kim, “An approach to
Korean license plate recognition based on vertical
edge matching”, IEEE International Conference on
System, Man
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Thank You
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