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Major Project Report on Number Plate Recognition System.

Aditya Mishra

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  1. 1. 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
  2. 2. 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
  3. 3. 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
  4. 4. VI Conclusion 23 to 24 Finding Conclusion Future Work Appendices 25 Refrences 26
  5. 5. ( 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
  6. 6. ( 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
  7. 7. ( 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
  8. 8. ( 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
  9. 9. ( 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
  10. 10. ( VII ) LIST OF TABLES Table 3.1 Risk and mitigation plan...................................................................................... 28 Table 4.2 Test Plan ................................................................................................................ 30 Table 4.3 Testing Environment ............................................................................................. 32
  11. 11. ( 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
  12. 12. 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
  13. 13. 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
  14. 14. 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
  15. 15. 4 Fig – Tabular comparison of technologies
  16. 16. 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 &arnumber=5403292
  17. 17. 6 Paper 2 Title of paper Optical Character Recognition Authors Ravina Mithe, Supriya Indalkar, Nilam Divekar Year of Publication 2013 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 32113.pdf
  18. 18. 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. Year of Publication 2014 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 matic.pdf
  19. 19. 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 Year of Publication 2011 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 pdf
  20. 20. 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
  21. 21. 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
  22. 22. 11 Fig 3- Windows Application Architecture
  23. 23. 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
  24. 24. 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.
  25. 25. 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.
  26. 26. 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
  27. 27. 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.
  28. 28. 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.
  29. 29. 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.
  30. 30. 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
  31. 31. 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
  32. 32. 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
  33. 33. 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
  34. 34. 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
  35. 35. 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.
  36. 36. 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
  37. 37. 26 References 1. 2. nfe rence+Publications&queryText%3Dplate+recognition+system 3. 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
  38. 38. ADITYA MISHRA College Address: Jaypee Institute of Information Technology, A-10,Sector-62 Noida-201307 Uttar Pradesh. Mob: +91-8130118550 Email: | 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. 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 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
  39. 39.  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. ( – 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. ( – 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  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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Major Project Report on Number Plate Recognition System. Aditya Mishra 9911102158


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