Automatic License Plate Recognition for Electronic Payment system Chiu Wing Cheung d.

Slides:



Advertisements
Similar presentations
CSE 424 Final Presentation Team Members: Edward Andert Shang Wang Michael Vetrano Thomas Barry Roger Dolan Eric Barber Sponsor: Aviral Shrivastava.
Advertisements

By: Mani Baghaei Fard.  During recent years number of moving vehicles in roads and highways has been considerably increased.
OpenCV Introduction Hang Xiao Oct 26, History  1999 Jan : lanched by Intel, real time machine vision library for UI, optimized code for intel 
Real time vehicle tracking and driver behavior monitoring using a cellular handset based on accelerometry and GPS data Kevin Burke 4 th Electronic and.
July 27, 2002 Image Processing for K.R. Precision1 Image Processing Training Lecture 1 by Suthep Madarasmi, Ph.D. Assistant Professor Department of Computer.
Compiled and Presented by KJ Tsiri Supervisor : Mr. Ismail.
OCRdroid : A Framework to Digitize Text Using Mobile Phones  Authors  Mi Zhang, Anand Joshi, Ritesh Kadmawala, Karthik Dantu, Sameera Poduri, and Gaurav.
Department of Electrical and Computer Engineering He Zhou Hui Zheng William Mai Xiang Guo Advisor: Professor Patrick Kelly ASLLENGE.
Move With Me S.W Graduation Project An Najah National University Engineering Faculty Computer Engineering Department Supervisor : Dr. Raed Al-Qadi Ghada.
Virtual Dart: An Augmented Reality Game on Mobile Device Supervisor: Professor Michael R. Lyu Prepared by: Lai Chung Sum Siu Ho Tung.
Automatic Parking Enforcer ENSC 440 Presentation and Demo December 13, 2010 Presented by: R.Maroufi, R.Johal, A.Moshgabadi, Y.Kuo, S.Rohani.
I see you… INTELLIGENT TRANSPORTATION SYSTEMS AS A MEANS OF AUTOMATIC ROAD ENFORCEMENT BY: KEVIN NICOLI.
HCI Final Project Robust Real Time Face Detection Paul Viola, Michael Jones, Robust Real-Time Face Detetion, International Journal of Computer Vision,
Real-time Embedded Face Recognition for Smart Home Fei Zuo, Student Member, IEEE, Peter H. N. de With, Senior Member, IEEE.
LYU0203 Smart Traveller with Visual Translator for OCR and Face Recognition Supervised by Prof. LYU, Rung Tsong Michael Prepared by: Wong Chi Hang Tsang.
Vision Computing An Introduction. Visual Perception Sight is our most impressive sense. It gives us, without conscious effort, detailed information about.
California Car License Plate Recognition System ZhengHui Hu Advisor: Dr. Kang.
Vision-Based Biometric Authentication System by Padraic o hIarnain Final Year Project Presentation.
Evaluating the use of OCR on a Mobile Device Presented by : Hamed Alharbi Supervisor by :Dr Brett Wilkinson.
Jason Li Jeremy Fowers Ground Target Following for Unmanned Aerial Vehicles.
Prepared by: - Mr. T.R.Shah, Lect., ME/MC Dept., U. V. Patel College of Engineering. Ganpat Vidyanagar. Digital Image Processing & Machine Vision – An.
Android Phone App JOHN MICHAEL MARIANO UNDERGRADUATE MECHANICAL ENGINEERING STUDENT EEL 4665 INTELLIGENT MACHINES DESIGN LABORATORY OCTOBER 30, 2014.
Casey Smith Doug Ritchie Fred Lloyd Michael Geary School of Electrical and Computer Engineering November 2, 2011 ECE 4007 Automated Speed Enforcement Using.
1PORTMANN PROJECT OVERVIEWMarch 2013 Canada, Vancouver Port Mann bridge Freeflow tolling operation.
By: Hadley Scholtz Supervisor: Mehrdad Ghaziasgar Co – supervisor: James Connan Assisted by: Ibraheem Frieslaar.
Update September 14, 2011 Adrian Fletcher, Jacob Schreiver, Justin Clark, & Nathan Armentrout.
An efficient method of license plate location Pattern Recognition Letters 26 (2005) Journal of Electronic Imaging 11(4), (October 2002)
Submitted by:- Vinay kr. Gupta Computer Sci. & Engg. 4 th year.
© 2008 Chen Hao, Beijing Institute of Technology 1 Intelligent Parking System: Parking Guide Application in Beijing and Method for License Plate Localization.
NATMEC June 5, 2006 Comparative Analysis Of Various Travel Time Estimation Algorithms To Ground Truth Data Using Archived Data Christopher M. Monsere Research.
 Supervised by Prof. LYU Rung Tsong Michael Student: Chan Wai Yeung ( ) Lai Tai Shing ( )
Intelligent Transportation System Oum Saokosal Cambodian Graduate Student April 2009.
Phone Reader Project Presenter: Marilyn Bihina Supervisor: James Connan.
MACHINE VISION Machine Vision System Components ENT 273 Ms. HEMA C.R. Lecture 1.
NEURAL - FUZZY LOGIC FOR AUTOMATIC OBJECT RECOGNITION.
Cloud Computing Applications Hsu, Ya-Lun. Google App Engine Using Python and Django Register applications for free from Google Run web applications on.
Casey Smith Doug Ritchie Fred Lloyd Michael Geary School of Electrical and Computer Engineering December 15, 2011 ECE 4007 Automated Speed Enforcement.
Compiled and Presented by KJ Tsiri Supervisor : Mr. Ismail.
Jack Pinches INFO410 & INFO350 S INFORMATION SCIENCE Computer Vision I.
Delivering Business Value through IT Face feature detection using Java and OpenCV 1.
Higher Vision, language and movement. Strong AI Is the belief that AI will eventually lead to the development of an autonomous intelligent machine. Some.
Virtual Image Peephole By Kyle Patience Supervisor: Reg Dodds Co Supervisor: Mehrdad Ghaziasgar.
Connor Carey. Aims  Record road scene from Android  Detect speed sign  Determine speed limit  Compare to current speed(GPS)  Alert driver if speeding.
Real-time foreground object tracking with moving camera P Martin Chang.
Copyright 2007 by Rombix. R CyClops is a computer vision solution which could integrate most of the Real World Computer Vision Application. Available.
Portable Camera-Based Assistive Text and Product Label Reading From Hand-Held Objects for Blind Persons.
An intelligent strategy for checking the annual inspection status of motorcycles based on license plate recognition Yo-Ping Huang a, Chien-Hung Chen b,
License Plate Recognition of A Vehicle using MATLAB
AUTOMATIC NUMBER PLATE RECOGNITION SYSTEM
Group Number5 Group Members Harsh AroraY08UC059 Mayank AgarwalY08UC079 Vishal BharadwajY08UC141 Automatic Number Plate Recognition.
Motion tracking TEAM D, Project 11: Laura Gui - Timisoara Calin Garboni - Timisoara Peter Horvath - Szeged Peter Kovacs - Debrecen.
LOGO AutoCarParking Capstone Project. LOGO Project Role HungPD Supervisor Huynb Project Manager, Developer Truongpx Developer Tuanhh Developer, tester.
Kbv Research | +1 (646) | Automatic Number Plate Recognition (ANPR) System Market Knowledge Based Value (KBV) Research Visit:
Hand Gestures Based Applications
Android Development 陆俊敏 F
Outline Introduction Standards Project General Idea
DESCRY: Design for Electrical Sensor Character Recognition Yoking
Mousavi,Seyed Muhammad – Lyashenko, Vyacheslav
Image Recognition. Contents: Motivation Objective Definition Introduction Preprocessing / Edge Detection Neural Networks in Image Recognition Practical.
bReader – Blind can read now
A language assistant system for smart glasses
Transact™ Mobile SDK Quickly bring capture-enabled mobile applications to market with open-ended backend integrations.
CS 7455 Term Project Robot control by Machine learning
Software engineering in the mobile phone platform war.
Developing an Android application for
Factors that Influence the Geometric Detection Pattern of Vehicle-based Licence Plate Recognition Systems Martin Rademeyer Thinus Booysen, Arno Barnard.
Object Recognition & Detection
Optical Character Recognition
Presentation transcript:

Automatic License Plate Recognition for Electronic Payment system Chiu Wing Cheung d

Outline Introduction Theories Methodology Results Applications Conclusion

Overview License plate recognition is the extraction of license plate information from camera It makes use of the technology of image processing, optical character recognition It plays an important role in Intelligent Transport System

Objectives To Study different algorithms of image processing To develop an android ANPR application using OpenCV and Tesseract To build a model to demonstrate the operations after the license plates are recognised

Theories Automatic Number Plate Recognition (ANPR) comprises of six stages

Image acquisition Camera is essential element of ANPR system Camera is used to capture image of vehicle containing license plate information Camera can be triggered by: 1.Hardware 2.Software 3.Free Flow

Image acquisition Hardware: Physical sensor like magnetic loop detector It is used to detect the existence of vehicles Software Movement detection Using several algorithms like background subtraction Free Flow Detect license plate continuously

Image Pre-processing Image capture need pre-processing To reduce the noise of background To sharpen plate information To enhance the processing speed of recognition

Plate localization Find the region of license plate as Region of Interest Eliminate the unwanted background Many algorithms for different features of license: Edge information Texture feature Colour feature

Character Segmentation Identify the contours of each character Distinguish each character by Image Scissoring algorithm To normalize characters Enhance the accuracy of Optical Character Recognition

Optical Character Recognition Generate the plate information from input image The basic process: 1.Samples of characters are input for training in advance 2.Input image of segment characters 3.Comparing input image with trained data 4.output the results

Methodology Android application development OpenCV Tesseract OCR Arduino

Android App Development Android is a Linux-kernelled mobile operating system Most Android phones contain cameras, CPU, Bluetooth and Wifi Android software development kit (SDK) provides platform for developers to build their own application Eclipse used as a IDE for develop ANPR application

OpenCV Open source library for computer vision Multiple interface like C++, C, and Python Provides thousands algorithms for image processing

Tesseract OCR Open source OCR engine sponsored by Google Provide trained data of different languages

System design

Results

Vertical Sobel Operator

Close Operation

Plate Localization

Real test

Real Test

OCR

Application Electronic Toll Payment Traffic Surveillance Parking Management System Traffic Law enforcement

Conclusion ANPR application has been developed on android phone making use of open source libraries. Different algorithms for image acquisition, image processing, plate detection, and character recognition has been implemented