Automatic Vehicle Identification Using Number Plate Recognition

NUMBER PLATE RECOGNITION SYSTEM USING OCR
Enrollment No.: 9911102158
Name of Student: Aditya Mishra
Name of Supervisor: Mr.Gaurav Saxena
June 2015
Submitted in partial fulfillment of the Degree of
Bachelor of Technology
in
Computer Science Engineering
DEPARTMENT OF COMPUTER SCIENCE & ENGINEERING JAYPEE
INSTITUTE OF INFORMATION TECHNOLOGY, NOIDA

TABLE OF CONTENTS
Chapter No. Topics Page No.
Table of Contents I
Student Declaration II
Certificate from the Supervisor III
Acknowledgement IV
Summary V
List of Figures VI
List of Tables VII
List of Symbols and Acronyms VIII
I Introduction Page No to Page No1 to 4
General Introduction
Problem Statement
Empirical Study.
Novelty/benefits
Comparison of existing approaches
II Background Study Page No to Page No5 to 9
Literature Survey
Summary of papers
Integrated summary of the literature studied

III Analysis, Design and Modeling 10 to 16
Overall Description of the project
Requirements Specifications
Functional and Non Functional requirements
Logical Database Requirement
Design Documentation
Use Case diagrams
Class diagrams / Control Flow Diagrams
Sequence Diagram/Activity diagrams
IV Implementation Details and Issue 17 to 20
Implementation details and issues
Algorithm
Risk Analysis and mitigation plan
V Testing 20 to 23
Testing Plan
Component decomposition and type of testing
required
List all test cases
Limitation

VI Conclusion 23 to 24
Finding
Conclusion
Future Work
Appendices 25
Refrences 26

( II )
DECLARATION
I hereby declare that this submission is my own work and that, to the best of my knowledge and
belief, it contains no material previously published or written by another person nor material which
has been accepted for the award of any other degree or diploma of the university or other institute of
higher learning, except where due acknowledgment has been made in the text.
Signature:
Place: Name: Aditya Mishra
Date: 1/6/2015 Enrollment No: 9911102158

( III )
CERTIFICATE
This is to certify that the work titled “ THE NUMBER PLATE RECOGNITION SYSTEM
USING OCR ” submitted by “Aditya Mishra” in partial fulfillment for the award of degree of
B. Tech In Computer Science and Engineering of Jaypee Institute of Information Technology
University, Noida, has been carried out under my supervision. This work has not been submitted
partially or wholly to any other University or Institute for the award of this or any other degree or
diploma.
Signature of Supervisor
Name of Supervisor Gaurav Saxena
Designation ASSISTANT PROFESSOR
Date 1/6/2015

( IV )
ACKNOWLEDGEMENT
I would like to place on record our deep sense of gratitude to Dr. Shelly Sachdeva, Professor,
Jaypee Institute of Information Technology, Noida, for her generous guidance. I express my sincere
gratitude to my mentor, Mr. Gaurav Saxena, Assistant Professor , Jaypee Institute of Information
Technology, Noida, I am grateful for his assistance, cooperation, stimulating guidance, continuous
encouragement and supervision throughout the course of present work.
Signature of the Student
Name Aditya Mishra
Enrollment Number 9911102158
Date 1/6/2015

( V )
SUMMARY
Automatic Number Plate Recognition (ANPR) is an image processing technology which uses
number (license) plate to identify the vehicle. The objective is to design an efficient automatic
authorized vehicle identification system by using the vehicle number plate. The system is
implemented on the
entrance for security control of a highly restricted area like military zones or area around top
government offices e.g. Parliament, Supreme Court etc. The developed captures the vehicle image.
Vehicle number plate region is extracted using the image segmentation in an image. Optical
character recognition technique is used for the character recognition. The resulting data is then used
to compare with the records on a database so as to come up with the specific information like the
vehicle’s owner, place of registration, address, etc. The system is implemented and simulated in
Android, and it performance is tested on real image. It is observed from the experiment that the
developed system successfully
Signature of Student Signature of Supervisor
Name: Aditya Mishra Name: Gaurav Saxena
Date: 3/1/2015 Date: 3/1/2015

( VI )
LIST OF FIGURES
Figure 1 Tabular Comparison ................................................................................................4
Figure 2 OCR Block Diagram ...............................................................................................10
Figure 3 Windows Application Architecture.........................................................................11
Figure 4 Mobile Application Architecture.............................................................................12
Figure 5 Use Case ..................................................................................................................15
Figure 6 Class Diagram..........................................................................................................16

( VII )
LIST OF TABLES
Table 3.1 Risk and mitigation plan...................................................................................... 28
Table 4.2 Test Plan ................................................................................................................ 30
Table 4.3 Testing Environment ............................................................................................. 32

( VIII )
LIST OF ACRONYMS AND SYMBOLS
ADK – Android Development Kit
SDK – Software Development Kit
GUI – Graphical User Interface
IDE – Integrated Development Environment
HTTP – Hyper Text Transfer Protocol
SQL – Sequential Query Language

1
Chapter 1: INTRODUCTION
1.1 General Introduction
Automatic number plate recognition (ANPR) is an image processing technology which uses number
(license) plate to identify the vehicle. The objective is to design an efficient automatic authorized
vehicle identification system by using the vehicle number plate. The system is implemented on the
entrance for security control of a highly restricted area like military zones or area around top
government offices e.g. Parliament, Supreme Court etc. This system can be used by every man for their
security purpose. For general public an android application will installed on their mobile phone. After
that whenever he wants to know the details of any vehicle he just have to capture the image of licence
plate and then that image will be processed and he will get the desired information about that vehicle.
This system is very important and must needed. For defence purposes the developed system first
detects the vehicle and then captures the vehicle image. Vehicle number plate region is extracted using
the image segmentation in an image. Optical character recognition technique (OCR) is used for the
character recognition. The resulting data is then used to compare with the records on a database so as to
come up with the specific information like the identity of owner, place of registration, address, etc. The
system is implemented and simulated in JAVA, and it performance is tested on real image.
Optical Character Recognition :
The goal of Optical Character Recognition (OCR) is to classify optical patterns (often contained in a
digital image) corresponding to alphanumeric or other characters. The process of OCR involves several
steps including segmentation, feature extraction, and classification. Each of these steps is a field unto
itself, and is described briefly here in the context of a Matlab implementation of OCR.
A few examples of OCR applications are listed here. The most common for use OCR is the first item;
people often wish to convert text documents to some sort of digital representation.
1. People wish to scan in a document and have the text of that document available in a word processor.
2. Recognizing license plate numbers

2
3. Image to speech conversion
1.2 Problem Statement
To Develop an android application to capture the image of the licence number plate and to obtain all
the information about that vehicle.
1.3 Empirical Study:
Optical character recognition, usually abbreviated to OCR, is the mechanical or electronic translation
of images of handwritten, typewritten or printed text (usually captured by a scanner) into machine-
editable text.
OCR is a field of research in pattern recognition, artificial intelligence and machine vision. Though
academic research in the field continues, the focus on OCR has shifted to implementation of proven
techniques. Optical character recognition (using optical techniques such as mirrors and lenses) and
digital character recognition (using scanners and computer algorithms) were originally considered
separate fields. Because very few applications survive that use true optical techniques, the OCR term
has now been broadened to include digital image processing as well.
Early systems required training (the provision of known samples of each character) to read a specific
font. "Intelligent" systems with a high degree of recognition accuracy for most fonts are now common.
Some systems are even capable of reproducing formatted output that closely approximates the original
scanned page including images, columns and other non-textual components.
The United States Postal Service has been using OCR machines to sort mail since 1965 based on
technology devised primarily by the prolific inventor Jacob Rabinow. The first use of OCR in Europe
was by the British General Post Office (GPO). In 1965 it began planning an entire banking system,
the National Giro, using OCR technology, a process that revolutionized bill payment systems in the
UK. Canada Post has been using OCR systems since 1971.
In 1974 Ray Kurzweil started the company Kurzweil Computer Products, Inc. and led development of
the first omni-font optical character recognition system — a computer program capable of recognizing
text printed in any normal font. He decided that the best application of this technology would be to
create a reading machine for the blind, which would allow blind people to have a computer read text to

3
them out loud. This device required the invention of two enabling technologies — the CCD flatbed
scanner and the text-to-speech synthesizer.
1992-1996 Commissioned by the U.S. Department of Energy (DOE), Information Science Research
Institute (ISRI) conducted the most authoritative of the Annual Test of OCR Accuracy for 5
consecutive years in the mid-90s. Information Science Research Institute (ISRI) is a research and
development unit of University of Nevada, Las Vegas. ISRI was established in 1990 with funding from
the U.S. Department of Energy. Its mission is to foster the improvement of automated technologies for
understanding machine printed documents.
One study based on recognition of 19th and early 20th century newspaper pages concluded that
character-by-character OCR accuracy for commercial OCR software varied from 71% to 98%; total
accuracy can only be achieved by human review. Other areas—including recognition of hand
printing, cursive handwriting, and printed text in other scripts (especially those East Asian language
characters which have many strokes for a single character)—are still the subject of active research.
1.4 Novelty of Problem
OCR technology has been used from time to time for various purposes. Various kinds of windows
application have been made till now. But using this technology and android together is a unique
concept. This kind of application is not made yet. The unique feature of this application is that it will
contain large amount of data. Anyone who want to know the detail of any vehicle can directly go to this
app and know the information. Even the Police can use this app to capture the criminals. By image they
will instantly know on whose name the vehicle is registered which is used by criminal. So the use of
technology for safety purpose is unique feature.
1.5 Tabular comparison of other existing approaches

4
Fig – Tabular comparison of technologies

5
Chapter-2: Literature Survey
2.1 Summary of paper studied
Research Papers
Paper 1
Title of paper AUTOMATIC NUMBER PLATE RECOGNITION SYSTEM FOR
VEHICLE IDENTIFICATION USING OPTICAL CHARACTER
RECOGNITION
Authors Muhammad Tahir Qadri, Muhammad Asif
Year of Publication 2009
Publishing details International Conference on Education Technology and Computer (IEEE)
Summary Automatic Number Plate Recognition (ANPR) is an
image processing technology which uses number (license) plate
to identify the vehicle. The objective is to design an efficient
automatic authorized vehicle identification system by using the
vehicle number plate. The developed system first
detects the vehicle and then captures the vehicle image. Vehicle
number plate region is extracted using the image segmentation
in an image. Optical character recognition technique is used
for the character recognition. The resulting data is then used to
compare with the records on a database so as to come up with
the specific information like the vehicle’s owner, place of
registration, address, etc.
Web link http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=
&arnumber=5403292

6
Paper 2
Title of paper Optical Character Recognition
Authors Ravina Mithe, Supriya Indalkar, Nilam Divekar
Publishing details International Journal of Recent Technology and Engineering (IJRTE)
Summary The Optical Character Recognition is a mobile
application. It uses smart mobile phones of android platform. This
paper combines the functionality of Optical Character
Recognition and speech synthesizer. The objective is to develop
user friendly application which performs image to speech
conversion system using android phones. The OCR takes image as
the input, gets text from that image and then converts it into
speech. This system can be useful in various applications like
banking, legal industry, other industries, and home and office
automation. It mainly designed for people who are unable to read
any type of text documents.
.
Web link http://www.ijrte.org/attachments/File/v2i1/A05040
32113.pdf

7
Paper 3
Title of paper Automatic license plate recognition using optical character
recognition and template matching on yellow color license plate
Authors Vandini Sharma,Prakash C. Mathpal, Akanksha
Kaushik.
Publishing details International Journal of Innovative Research in Science,
Engineering and Technology
Summary Automatic license plate recognition is used to recognize the
characters from license plate image. It is
widely used in various areas such as traffic control, robbery, and
surveillance. The proposed method applied on
yellow color license plate. It has two main stages. Firstly, exact
location of the license plate is detected from an input
image by using image acquisition and optical character recognition
and Sobel edge is used for character
segmentation. Secondly, template matching is used to test the
recognized characters with templates.
Web link http://www.ijirset.com/upload/2014/may/111_Auto
matic.pdf

8
Paper 4
Title of paper Design of an Optical Character Recognition System for Camera-
based Handheld Devices
Authors
Ayatullah Faruk Mollah, Nabamita Majumder ,Subhadip Basu, and
Mita Nasipuri
Publishing details International Journal of Computer Science Issues
Summary This paper presents a complete Optical Character Recognition
(OCR) system for camera captured image/graphics embedded textual
documents for handheld devices. At first, text regions are extracted
and skew corrected. Then, these regions are binarized and segmented
into lines and characters. Characters are passed into the recognition
module.. Compared to Tesseract, an open source desktop-based
powerful OCR engine, present recognition accuracy is worth
contributing. Moreover, the developed technique is computationally
efficient and consumes low memory so as to be applicable on
handheld devices.
Web link http://arxiv.org/ftp/arxiv/papers/1109/1109.3317.
pdf

9
2.3 Integrated Summary of Literature Studied:
Topic Result
AUTOMATIC NUMBER PLATE RECOGNITION SYSTEM FOR
VEHICLE IDENTIFICATION USING OPTICAL CHARACTER
RECOGNITION
Optical Character Recognition
Automatic license plate recognition using optical character recognition
and template matching on yellow color license plate
Different techniques are
studied and analyzed i.e.
Yellow search Algorithm,
Smearing algorithm.
Configuring camera
devices to computer and to
use them.
How to implement ocr on
android phone.
Table1: Integrated Summary

10
Chapter-3: Analysis, Design and Modeling
3.1 Overall description of the project
On Line / Real Time Input
Off Line Input
Fig 2 : OCR Block Diagram
Touch Pad
PC
Scanned Document
Stored
Characters
Grayscale
Conversion
Filtering
Thinning
Feature
Extraction
Pattern Recognition
Recognition
Output
Software Domain

11
Fig 3- Windows Application Architecture

12
Fig 4 - Mobile Application Architecture
Requirements Specifications for windows Application
Hardware Requirements
 Hard disk: 10 GB minimum
 Ram: 1GB minimum
 3 mega pixel camera
 Mouse
 Keyboard

13
 Scanner and Monitor
Software Requirements
 System Type: 64-bit operating system,x-64 based processor
 OS Installed: Windows XP or higher
 Matlab installed
Requirements Specifications for mobile Application
Mobile Hardware Requirements
 ARM 11 processor or higher
 Memory 1 GB
 256 MB RAM
 Mobile camera 5 Mega pixel
Software Requirements
 JAVA – J2ME and J2EE
 Operating System-Android Mob OS
3.2 Functional requirements :
1. For static OCR, software should provide a way to load scanned document for recognition
purpose.
2. If scanned image is not having black background and white foreground, facility for image
inversion should be provided by software.
3. Software should process the image and extract characters.
4. User should have facility to save extracted data in format of his interest.
5. For dynamic OCR, the software should recognize characters drawn by user simultaneously.
6. If software is not giving proper output, there should be a way for training the database of
software.

14
Other Requirements:
 Considerable amount of training data set
 The input image is to be in the RGB file format
 In case of scanned image, a high quality scanner as well as good paper quality is required. The
resolution of the scanner should be set to a minimum of 300 dots per inch (dpi)..
 A first order median filter is used
3.3 Non-Functional Requirements
• Reliability: The system is highly reliable.
• Accessibility: It can be easily accessible i.e click & run.
• Efficiency: Resource consumption for given load is quite low.
• Fault tolerance: Our system is not fault tolerant due to insufficient hardware.
• Robustness: Our system is not capable to cope with errors during execution.
• Scalability: Our project is scalable i.e. we can add more resources to our project without
disturbing the current scenario.
3.4 Logical Database Requirement
SQLite
The system must store all the user information. All the data shall be stored in text-based flat .sqlite
files. For each registered vehicle, name, license number, criminal record shall be stored in one file.

15
3.5 Design Diagrams
3.5.1 USE-CASE DIAGRAMS
Our software system can be used to support library environment to create a Digital Library where
several licence plate images are converted into electronic-form for accessing by the users. For this
purpose the printed plates must be recognized before they are converted into electronic-form. The
resulting electronic-documents are accessed by the users like police and general public for reading
and getting information.
Figure 5: Use case Diagram

16
3.3.2 Class Diagram
The class diagram gives a clear picture of all the processes involved in the background in
order to carry out the recognition process. It shows all the classes that happens in the
background and as well gives a clear relationship on how they relates with one another to
help recognize the characters in the plates at the end of the day. The class diagram contains
of all the attributes involved in each class or method. It also gives a high clear idea towards
the entire processing of the image, how the image is being processes to cater for recognizing
the characters.

17
Figure : Class Diagram
Chapter 4 IMPLEMENTATION DETAILS AND ISSUES
4.1 Implementation
The LPI android application is designed from a user point of view as well as government point of view.
The user friendly design helps the users in accomplishing their task with ease. Attempts have been
made to keep the design simple and understandable.
The screens were designed in XML and the business logic was written in Java. The database used is
SQLite where all the local information related to the users is stored.
The total lines of code written in this application is
Language LOC
Java 1400
XML 42
Table 4.1 Lines of Code
Debugging of the application throughout the development is done using Dalvik Debug Monitor Server
(DDMS). DDMS provides port-forwarding services, screen capture on the device, thread and heap
information on the device, logcat, process, and radio state information.
Graphical User Interface
The user interface is kept simple and understandable. The user need not take any additional effort to
understand the functionality and navigation in the application. The colors are chosen in such a way that
user can easily understand where the input has to be given. Hints are given to help the user in giving
the correct input.

18
The following are the main screens and features in this application.
• Home Screen
• Capture Image screen
• Text Screen
• Result Screen
4.1.2 Algorithm
Yellow Search Algorithm :
A yellow search algorithm is used to extract the likelihood ROI in an image. As number plate of is
in yellow background with alphanumeric character written in black, it is easy to detect the plate area by
searching for yellow pixels. The image is search for the yellow colour pixels or some which are closer
to yellow in value. If pixel value is of yellow colour the pixel is set to 1, otherwise the pixel value is set
to 0. The image obtained after the search algorithm is in black and white format.
Edge Detection :
Algorithms for edge detection contain three steps:
• Filtering (removing): Filtering reduces noise.
• Enhancement: Enhancement emphasizes pixels where there is a significant change in local intensity
values and is usually performed by computing the gradient magnitude.
• Detection: Many points in an image have a nonzero value for the gradient, but not all these points can
be considered to be edges. Therefore, some method should be used to determine which points are edge
points.
Frequently, thresholding provides the criterion for detection.
Preprocessing
The major cause of failure in detecting the number plate from the vehicle is low quality of image. The
preprocessing algorithm helps in improving the quality of the image or the plate image being inputted
to the system.

19
This involves:
• Resize
This involves resizing the image that is been taken for optimization purposes. Resizing is helpful since
image quality differs and in order to localize the number plate or be able to recognize the number plate
on the image resizing will be very helpful.
• Grayscale
4.2 Risk Analysis and Mitigation Plan
Risk
Id
Classification Description of risk Risk area Probability
(P)
Impact(I) Re(P*I)
1 Hardware Incapability of hardware
like RAM, Processor,
Memory etc
Performance,
hardware,
Time
High high 8.1
2 Multitenancy
(Shared
access)
All the users are using
the same physical
architecture
Security Low Low 0.1
3 Security Critical Data at risk Security High Medium 8.1
4 Security Authentication,
authorization, and access
control
User, Project
Scope, Time
High High 8.1
5 Hardware Processor Performance,
Time
Low High 0.9
6 Ownership User the owner of data Security High Low 0.9
7 Environment Windows Performance,
Time
High Medium 8.1

20
8 Personnel
Related
Incompetent Skills Time High High 8.1
9 Personnel
Related
Irregularity Time Medium High 2.7
Table3: Risk
Analysis
RATING IMPACT PROBABILITY
HIGH 9 0.9
MEDIUM 3 0.3
LOW 1 0.1
Table4: Impact
Risk Mitigation Plan
Hardware Hardware related issues can be resolved by
using powerful processors support, Faster
RAMs and Bigger Storage device.
Security Secure connection must be established.
Personnel Related We will try to avoid irregularity.
Environments ARM must be installed on mobile.
Table6: Mitigation Plan

21
Chapter 5: Testing
5.1 Testing Plan
Type of Test Will it be
performed?
EXPLANATIONS Software Component
Requirement
Testing
Yes Requirements specification must
contain all the requirements that are
to be solved by our system.
Manual work, need to
plan out all the software
requirements, time needed
to develop, technology to be
used etc.
Unit Yes Testing by which individual units of
source code are tested to determine
Manual check is required
3
0

22
if they are fit for use.
Integration Yes Testing wherein individual
components are combined and tested
as a group.
Compiling full part of the
code and testing it together.
Performance Yes Testing to evaluate the input where
the best and most optimal output is
Yielded by the system.
Protocols used ensures
this.
Stress Yes Simulating beyond normal Operational
capacity.
heavy data files .
Compliance No Not needed NA
Volume
Volume
yes
Yes
Large volume of Data
NA
The protocol ensures this.
5.2 Component decomposition and type of testing required
S.No. Various components
that require testing
Type of testing
required
Technique for
writing Test cases
1 API Implemented Unit, Performance,
Volume, Security
White box
2 Database analysis
and results
Unit, Performance,
Stress
Black box

23
3 Eclipse tool and
results
Unit, Performance,
Integration
White box
Table4 : Testing Components
5.3 List all test cases
S.No. Input Output Status
1 Activate the LPI software and
execute the app for capturing
image.
App Capture image
without error
Pass
2 Text Extraction Desired outputs
accordingly
Pass
3 Database Analysis Database Matched Pass
Table5 : Test Cases
5.4 Limitations
 The application can capture certain portion of image only. Large image should be
cropped.
 Camera should be of good quality. Otherwise correct text from image would not be
extracted properly.
 There should be proper lighting.
3

24
Chapter-6: Conclusion
6.1 Finding
There are various ANPR applications that are already present but they do not contain man
features. Text extraction applications lack the user friendly environment hence in this
application a lot is concentrated on the user friendly environment. There is no android
application available out there. It’s first of its kind.
6.2 Conclusion
In this project, we aimed to develop a plate recognition system using OCR in android and
windows. We got images by capturing images through a camera without noise and tried to
read characters from that image .Android platform is used because of its availability. Every
person nowadays has android cell phone. There any one can use this application through it.So
for user it is very We will also make Mobile application to detect number Plate using OCR.
6.3 Future Work
The application can be improved in many ways and can be extended to support more devices
like the tablets and iOS devices.
The application will also support blurry images or not so good quality images.
More detailed information regarding the number plate will be available.
People can register and put the information on there own
Registering application with Google service and uploading it into Google Play Store.

25
(IX)
APPENDIX
Project Plan
Jan '15
•Finding a way to combine interest and mobile computing
Feb'15
Q1
•Learning all about android
•Learning how to use eclipse
Mar'15
•Designing the interface of mobile application
Mar' 15
•Exploring the content for the application
Apr' 15
•Testing the application
May' 15
•Including the option for saving data in SQLite database to
access posts when offline
May' 15
• Making it more user friendly
• Including comments functionality
Jun' 15
• Testing and Enhancement

26
References
1.http://www.ele.uri.edu/~hansenj/projects/ele585/OCR/OCR.pdf
2.http://ieeexplore.ieee.org/xpl/articleDetails.jsp?tp=&arnumber=5169511&contentType=Co
nfe rence+Publications&queryText%3Dplate+recognition+system
3. http://www.mathworks.com/products/matlab/
4.Gonzalez, R.C. And Woods, R.E.,1992 Digital image Proccessing, AddisonWesley
Publishing Company Inc., UK
5.J.T. Tou and R.C. Gonzalez, Pattern Recognition Principles, Addison-Wesley Publishing
Company, Inc., Reading, Massachusetts, 1974

ADITYA MISHRA
College Address: Jaypee Institute of Information Technology,
A-10,Sector-62 Noida-201307 Uttar Pradesh.
Mob: +91-8130118550
Email: adi.mishra@outlook.com | adi1016@gmail.com
Career Objective: To enhance capabilities and skills through a continuous process of learning, following a logical and
humanitarian approach in life, proving efficiency, keeping in view the importance of time for the organization, and
through which reaching greater heights in life.
Software Proficiency:
 Knowledge of programming languages C, C++,PHP,Mysql
 Knowledge of DBMS and SQL.
 Knowledge and experience in Web Development, Content management systems and languages like HTML, CSS
and basics of Java Scripts ,Android Application development.
Educational Qualification:
JAYPEE INSTITUTE OF INFORMATION TECHNOLOGY
Bachelor of Technology, July 2011 – May 2015 (Expected)
Currently pursuing B. Tech, VIII semester in the Department of Computer Engineering
Cumulative GPA: 5.2/10 which is equivalent to 61%
Montfort Inter College, Mahanagar, Lucknow
Intermediate (Class XII) - U.P. STATE BOARD
Percentage: 76%
Montfort Inter College, Mahanagar, Lucknow
High School (Class X) - U.P. STATE BOARD
Percentage: 78%
Work Experience (Internships & Projects):
 Summer Intern at MTAIndia, Technology Division, worked on developing Online Dictionary.
 Summer Intern at HPES, Technology Division, worked on developing Online Student Portal.
 Web development member at JIIT, worked in developing an interface front end for the college fest website’s
home page, etc. as per the requirements and backend customization for the website www. Converge13.com
Project Undertaken:
 Currently working on developing an android application “Number Plate Recognition using OCR”.
In this Project I will develop a mobile application which will capture the picture of any vehicle. After the picture is
captured its number plate image will be converted to text and then we will get the details like on whose name the
vehicle is registered etc.
 Major project on “Stock Market Prediction using Sentiment Analysis” under Mr. Gaurav Saxena, Department of
Computer Science Engineering, Jaypee Institute of Information Technology, Noida.
In this project I created a software using PHP language which will take any word(s) as input and will give all the
tweets related to that keyword .I hosted this tool on live server awsums.com. After getting all the related tweets I
pass them to a classifier which will classify the tweet into positive, negative or neutral. And then by analyzing we can
assume whether the market is going down or going up.
 Successfully completed a mini project on "Connect Street" an android application for buyer to track moving vendor
under Mr.Himanshu Mittal, Professor at Department of CSE, JIIT Noida.
In this project I developed an application which will track down nearest hospitals, restaurants ,or moving vendors
and will give direction to reach them

 Successfully completed a mini project on "Student Portal" a website for college to keep record of their students
attendance and student can prepare for higher studies using this portal under Ms.Aksansha Bharadwaj, Professor at
Department of CSE, JIIT Noida.
An initiative to develop a dedicated student level network which supports sharing of academic material among
students so as to facilitate useful information interchange and minimize academic problems.
(http://www.23ads.com) – Developed the whole portal on my own.
Fatshops, is a student entrepreneurial initiative which aims to develop a one stop online shopping portal designed
especially for people who wants to shop online at low price. (http://www.Fatshops.com.) – Developed the whole
website on my own within a very short span of time to quickly open operations for awaiting users.
Achievements:
 Organized Inter college Logo Quiz event at Techno-cultural fest Converge of JIIT.
 Part of Web Developer team of the cultural fest Converge at JIIT.
 Member of the Cricket Team of JIIT.
 Awarded with a scholarship by U.P Board for meritorious performance in High School examination.
 Won prizes in various competitions like ,Collage Making, Just-A-Minute, and designing events and thereby
Acquiring real-time experience of technical skills, public speaking, crises management and building public relations.
 Ability to work in multi-culture and multi-functional team environment as found in my own college JIIT where I
created a culturally and regionally diverse team for awsumz.com
 Passionate about using internet & playing table tennis and cricket.
Personal Profile:
Name : Aditya Mishra
Father : Ashok Kumar Mishra, Legal Advisor, Lucknow University, Lucknow.
Mother : Uma Mishra ,Bank Manager, Gramin Bank of Aryavrat,Lucknow.
D.O.B. : 12th of Feb, 1994
Nationality : Indian
Home Address : 2/315,Vivek Khand ,Gomti Nagar, Lucknow – 226010. (U.P)
(Aditya Mishra)

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