This document describes a project to develop a vehicle license plate recognition system using MATLAB for image and video processing. The system takes images of license plates as input, performs pre-processing like resizing, filtering and thinning, segments the license plate using horizontal and vertical analysis, and recognizes characters using template matching. It is intended to identify stolen vehicles, catch traffic violations, and enable automated toll collection and vehicle authentication. The system was implemented and tested on images and video frames captured in real environments. Future work could improve nighttime performance and avoid multiple matches or overlapped plates.
Automatic Car Number Plate Detection and Recognition using MATLABHimanshiSingh71
Car Number Plate Recognition and Detection (ANPRD) using MATLAB. This is MATLAB based project.
Take an input from user than convert it into gray scale image and then applying morphological operations and many more functions.
Automatic Car Number Plate Detection and Recognition using MATLABHimanshiSingh71
Car Number Plate Recognition and Detection (ANPRD) using MATLAB. This is MATLAB based project.
Take an input from user than convert it into gray scale image and then applying morphological operations and many more functions.
Automatic number plate recognition using matlabChetanSingh134
The project is based on Image processing.It basically detects the number plate while following an algorithm based on image processing.It does that by following certain steps like image detection, character segmentation, OCR, and template matching.Have a look at the ppt and you will understand each step clearly
License Plate Recognition System using Python and OpenCVVishal Polley
License plate recognition (LPR) is a type of technology, mainly software, that enables computer systems to read automatically the registration number (license number) of vehicles from digital pictures.
This Presentation is for project work which will work on the "FACE DETECTION USING MATLAB".
This presentation will be prepared on the practical basis instead of theoretical knowledge. So result may vary on the basis of your practical work.
This Presentation is of standard format which is also beneficial for the engineering student for project work.
Automatic Number Plate Recognition (ANPR) is a highly accurate system capable of reading vehicle number plates without human intervention through the use of high speed image capture with supporting illumination, detection of characters within the images provided, verification of the character sequences as being those from a vehicle license plate, character recognition to convert image to text; so ending up with a set of metadata that identifies an image containing a vehicle license plate and the associated decoded text of that plate.
Abstract:
With an everyday increase in the number of cars on our roads and highways, we are facing numerous problems, for example:
• Smuggling of cars
• Invalid license plates
• Identification of stolen cars
• Usage of cars in terrorist attacks/illegal activities
In order to address the above issues, we took up the project of developing a prototype, which can perform license plate recognition (LPR). This project, as the name signifies, deals with reading, storing and comparing the license plate numbers retrieved from snapshots of cars to ensure safety in the country and ultimately help to reduce unauthorized vehicles access and crime.
License Plate Recognition (LPR) has been a practical technique in the past decades. It is one of the most important applications for Computer Vision, Patter Recognition and Image Processing in the field of Intelligent Transportation Systems (ITS).
Generally, the LPR system is divided into three steps, license plate locating, license plate character segmentation and license plate recognition. This project discusses a complete license plate recognition system with special emphasis on the Localization Module.In this study, the proposed algorithm is based on extraction of plate region using morphological operations and shape detection algorithms. Segmentation of plate made use of horizontal and vertical smearing and line detection algorithms. Lastly, template matching algorithms were used for character recognition.
The implementation of the project was done in the platforms of Matlab and OpenCV.
Number Plate Recognition for Indian Vehiclesmonjuri10
This paper presents Automatic Number Plate
extraction, character segmentation and recognition for
Indian vehicles. In India, number plate models are not
followed strictly. Characters on plate are in different
Indian languages, as well as in English. Due to variations
in the representation of number plates, vehicle number
plate extraction, character segmentation and recognition
are crucial. We present the number plate extraction,
character segmentation and recognition work, with english
characters. Number plate extraction is done using Sobel
filter, morphological operations and connected component
analysis. Character segmentation is done by using
connected component and vertical projection analysis.
Character recognition is carried out using Support Vector
machine (SVM). The segmentation accuracy is 80% and
recognition rate is 79.84 %.
AUTOMATIC LICENSE PLATE RECOGNITION SYSTEM FOR INDIAN VEHICLE IDENTIFICATION ...Kuntal Bhowmick
Automatic License Plate Recognition (ANPR) is a practical application of image processing which uses number (license) plate is used to identify the vehicle. The aim is to design an efficient automatic vehicle identification system by using the
vehicle license 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.
It is worth mentioning that there is a scarcity in researches that introduce an automatic number plate recognition for indian vechicles.In this paper, a new algorithm is presented for Indian vehicle’s number plate recognition system. The proposed algorithm consists of two major parts: plate region extraction and plate recognition.Vehicle number plate region is extracted using the image segmentation in a vechicle image.Optical character recognition technique is used for the character recognition. And finally the resulting data is used to compare with the records on a database so as to come up with the specific information like the vehicle’s owner, registration state, address, etc.
The performance of the proposed algorithm has been tested on real license plate images of indian vechicles. Based on the experimental results, we noted that our algorithm shows superior performance special in number plate recognition phase.
Intelligent traffic information and control systemSADEED AMEEN
As the problem of urban traffic congestion spreads, there is a pressing need for the introduction of advanced technology and equipment to improve the state of the art of traffic control. In current situation, the signal remains green until the present cars have passed. To avoid those problems we propose a system for controlling the traffic light by image processing. The system will detect vehicles through images instead of using electronic sensors embedded in the pavement. A camera will be installed alongside the traffic light. It will capture image sequences. For this purpose, edge detection has been carried out and according to percentage of matching traffic light-durations can be controlled. In addition, when an emergency vehicle is approaching the junction, it will communicate to the traffic controller in the junction to turn ON the green light. This module uses ZigBee modules for wireless communications between the ambulance and traffic controller. Intelligent traffic control system helps to pass emergency vehicles smoothly. Traffic signal management system is developed for the traffic police, to control the traffic lights manually. Additionally an information system is added using a chat bot module to avail traffic information to user.
ER Publication,
IJETR, IJMCTR,
Journals,
International Journals,
High Impact Journals,
Monthly Journal,
Good quality Journals,
Research,
Research Papers,
Research Article,
Free Journals, Open access Journals,
erpublication.org,
Engineering Journal,
Science Journals,
Automatic number plate recognition using matlabChetanSingh134
The project is based on Image processing.It basically detects the number plate while following an algorithm based on image processing.It does that by following certain steps like image detection, character segmentation, OCR, and template matching.Have a look at the ppt and you will understand each step clearly
License Plate Recognition System using Python and OpenCVVishal Polley
License plate recognition (LPR) is a type of technology, mainly software, that enables computer systems to read automatically the registration number (license number) of vehicles from digital pictures.
This Presentation is for project work which will work on the "FACE DETECTION USING MATLAB".
This presentation will be prepared on the practical basis instead of theoretical knowledge. So result may vary on the basis of your practical work.
This Presentation is of standard format which is also beneficial for the engineering student for project work.
Automatic Number Plate Recognition (ANPR) is a highly accurate system capable of reading vehicle number plates without human intervention through the use of high speed image capture with supporting illumination, detection of characters within the images provided, verification of the character sequences as being those from a vehicle license plate, character recognition to convert image to text; so ending up with a set of metadata that identifies an image containing a vehicle license plate and the associated decoded text of that plate.
Abstract:
With an everyday increase in the number of cars on our roads and highways, we are facing numerous problems, for example:
• Smuggling of cars
• Invalid license plates
• Identification of stolen cars
• Usage of cars in terrorist attacks/illegal activities
In order to address the above issues, we took up the project of developing a prototype, which can perform license plate recognition (LPR). This project, as the name signifies, deals with reading, storing and comparing the license plate numbers retrieved from snapshots of cars to ensure safety in the country and ultimately help to reduce unauthorized vehicles access and crime.
License Plate Recognition (LPR) has been a practical technique in the past decades. It is one of the most important applications for Computer Vision, Patter Recognition and Image Processing in the field of Intelligent Transportation Systems (ITS).
Generally, the LPR system is divided into three steps, license plate locating, license plate character segmentation and license plate recognition. This project discusses a complete license plate recognition system with special emphasis on the Localization Module.In this study, the proposed algorithm is based on extraction of plate region using morphological operations and shape detection algorithms. Segmentation of plate made use of horizontal and vertical smearing and line detection algorithms. Lastly, template matching algorithms were used for character recognition.
The implementation of the project was done in the platforms of Matlab and OpenCV.
Number Plate Recognition for Indian Vehiclesmonjuri10
This paper presents Automatic Number Plate
extraction, character segmentation and recognition for
Indian vehicles. In India, number plate models are not
followed strictly. Characters on plate are in different
Indian languages, as well as in English. Due to variations
in the representation of number plates, vehicle number
plate extraction, character segmentation and recognition
are crucial. We present the number plate extraction,
character segmentation and recognition work, with english
characters. Number plate extraction is done using Sobel
filter, morphological operations and connected component
analysis. Character segmentation is done by using
connected component and vertical projection analysis.
Character recognition is carried out using Support Vector
machine (SVM). The segmentation accuracy is 80% and
recognition rate is 79.84 %.
AUTOMATIC LICENSE PLATE RECOGNITION SYSTEM FOR INDIAN VEHICLE IDENTIFICATION ...Kuntal Bhowmick
Automatic License Plate Recognition (ANPR) is a practical application of image processing which uses number (license) plate is used to identify the vehicle. The aim is to design an efficient automatic vehicle identification system by using the
vehicle license 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.
It is worth mentioning that there is a scarcity in researches that introduce an automatic number plate recognition for indian vechicles.In this paper, a new algorithm is presented for Indian vehicle’s number plate recognition system. The proposed algorithm consists of two major parts: plate region extraction and plate recognition.Vehicle number plate region is extracted using the image segmentation in a vechicle image.Optical character recognition technique is used for the character recognition. And finally the resulting data is used to compare with the records on a database so as to come up with the specific information like the vehicle’s owner, registration state, address, etc.
The performance of the proposed algorithm has been tested on real license plate images of indian vechicles. Based on the experimental results, we noted that our algorithm shows superior performance special in number plate recognition phase.
Intelligent traffic information and control systemSADEED AMEEN
As the problem of urban traffic congestion spreads, there is a pressing need for the introduction of advanced technology and equipment to improve the state of the art of traffic control. In current situation, the signal remains green until the present cars have passed. To avoid those problems we propose a system for controlling the traffic light by image processing. The system will detect vehicles through images instead of using electronic sensors embedded in the pavement. A camera will be installed alongside the traffic light. It will capture image sequences. For this purpose, edge detection has been carried out and according to percentage of matching traffic light-durations can be controlled. In addition, when an emergency vehicle is approaching the junction, it will communicate to the traffic controller in the junction to turn ON the green light. This module uses ZigBee modules for wireless communications between the ambulance and traffic controller. Intelligent traffic control system helps to pass emergency vehicles smoothly. Traffic signal management system is developed for the traffic police, to control the traffic lights manually. Additionally an information system is added using a chat bot module to avail traffic information to user.
ER Publication,
IJETR, IJMCTR,
Journals,
International Journals,
High Impact Journals,
Monthly Journal,
Good quality Journals,
Research,
Research Papers,
Research Article,
Free Journals, Open access Journals,
erpublication.org,
Engineering Journal,
Science Journals,
An Efficient Model to Identify A Vehicle by Recognizing the Alphanumeric Char...IJMTST Journal
Automatic Engine Number Recognition (AENR) is the digital image processing and an important aspect/role to identify the theft vehicles by recognizing characters, digits and special symbols. There is increase in the theft of vehicles, so to identify these theft vehicles, the proposed system is introduced. The proposed system controls the theft vehicles by recognizing a digits and characters in the number plate and chassis region and stores in the database in ASCII format to check the theft vehicles are registered or unregistered. Both system consists of 4 common phases: - Preprocessing, Character Extraction (ROI), Character Segmentation, and Character Recognition. This paper proposes a new scheme for engine number and chassis number extraction from the pre-processed image of the vehicle’s engine and chassis region using preprocess techniques, Region of Interest(ROI), Binarization, thresholding, template matching.
The ANPR (Automatic Number Plate Recognition) using ALR (Automatic line
Tracking Robot) is a system designed to help in recognition of number plates of vehicles.
This system is designed for the purpose of the security and it is a security system.
For more details
http://projectsofashok.blogspot.com/2010/04/anprautomatic-number-plate-recognition.html
Automated License Plate Recognition for Toll Booth ApplicationIJERA Editor
This paper describes the Smart Vehicle Screening System, which can be installed into a tollbooth for automated recognition of vehicle license plate information using a photograph of a vehicle. An automated system could then be implemented to control the payment of fees, parking areas, highways, bridges or tunnels, etc. There are considered an approach to identify vehicle through recognizing of it license plate using image fusion, neural networks and threshold techniques as well as some experimental results to recognize the license plate successfully.
Mobile Based Application to Scan the Number Plate and To Verify the Owner Det...inventionjournals
Any License plate recognition system usually passes through three steps of image processing: 1) Extraction of a license plate region; 2) Segmentation of the plate characters; and 3) Recognition of each character. A number of algorithms have been proposed in recent times for efficient disposal of the application. The purpose of this project was to develop a real time application which recognizes number plates from cars at a gate, for example at the entrance of a parking area or a border crossing. The system, based on regular PC with mobile camera, catches video frames which include a visible car number plate and processes them. Once a number plate is detected, its digits are recognized, displayed on the User Interface or checked against a database.The software aspect of the system runs on mobile hardware and can be linked to other applications or databases. It first uses a series of image manipulation techniques to detect, normalize and enhance the Image of the number plate, and then optical character recognition (ocr) to extract the alpha numeric text of number plate. The system are generally deployed in one of two basic approaches: one allows for the entire process to be performed at the lane location in real-time. The other will reveal the driver’s profile by checking in the registered database.
Vehicle Number Plate Recognition using MATLABAI Publications
The VPR (Vehicle Number plate Recognition) system is based on image processing technology. It is one of the necessary systems designed to detect the vehicle number plate. In today’s world with the increasing number of vehicle day by day it’s not possible to manually keep a record of the entire vehicle. With the development of this system it becomes easy to keep a record and use it whenever required. The main objective here is to design an efficient automatic vehicle identification system by using vehicle number plate. The system first would capture the vehicles image as soon as the vehicle reaches the security checking area. The captured images are then extracted by using the segmentation process. Optical character recognition is used to identify the characters. The obtained data is then compared with the data stored in their database. The system is implemented and simulated on MATLAB and performance is tested on real images. This type of system is widely used in Traffic control areas, tolling, parking area .etc. This system is mainly designed for the purpose of security system. Basically video surveillance system is used for security purpose as well as monitoring systems. But Detection of moving object is a challenging part of video surveillance. Video surveillance system is used for Home security, Military applications, Banking /ATM security, Traffic monitoring etc. Now a day’s due to decreasing costs of high quality video surveillance systems, human activity detection and tracking has become increasingly in practical. Accordingly, automated systems have been designed for numerous detection tasks, but the task of detecting illegally parked vehicles has been left largely to the human operators of surveillance systems. The detection of Indian vehicles by their number plates is the most interesting and challenging research topic from past few years.
it is about the basic of MATLAB and a project on MATLAB IMAGE PROCESSING (NUMBER PLATE DETECTION SYSTEM).It will help u to understand the basic concept ot MATLAB
Automatic License Plate Recognition using OpenCVEditor IJCATR
Automatic License Plate Recognition system is a real time embedded system which automatically recognizes the license plate of vehicles. There are many applications ranging from complex security systems to common areas and from parking admission to urban traffic control. Automatic license plate recognition (ALPR) has complex characteristics due to diverse effects such as of light and speed. Most of the ALPR systems are built using proprietary tools like Matlab. This paper presents an alternative method of implementing ALPR systems using Free Software including Python and the Open Computer Vision Library.
Automatic License Plate Recognition using OpenCV Editor IJCATR
Automatic License Plate Recognition system is a real time embedded system which automatically recognizes the license plate of vehicles. There are many applications ranging from complex security systems to common areas and from parking admission to urban traffic control. Automatic license plate recognition (ALPR) has complex characteristics due to diverse effects such as of light and speed. Most of the ALPR systems are built using proprietary tools like Matlab. This paper presents an alternative method of implementing ALPR systems using Free Software including Python and the Open Computer Vision Library.
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...UiPathCommunity
💥 Speed, accuracy, and scaling – discover the superpowers of GenAI in action with UiPath Document Understanding and Communications Mining™:
See how to accelerate model training and optimize model performance with active learning
Learn about the latest enhancements to out-of-the-box document processing – with little to no training required
Get an exclusive demo of the new family of UiPath LLMs – GenAI models specialized for processing different types of documents and messages
This is a hands-on session specifically designed for automation developers and AI enthusiasts seeking to enhance their knowledge in leveraging the latest intelligent document processing capabilities offered by UiPath.
Speakers:
👨🏫 Andras Palfi, Senior Product Manager, UiPath
👩🏫 Lenka Dulovicova, Product Program Manager, UiPath
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
Key Trends Shaping the Future of Infrastructure.pdfCheryl Hung
Keynote at DIGIT West Expo, Glasgow on 29 May 2024.
Cheryl Hung, ochery.com
Sr Director, Infrastructure Ecosystem, Arm.
The key trends across hardware, cloud and open-source; exploring how these areas are likely to mature and develop over the short and long-term, and then considering how organisations can position themselves to adapt and thrive.
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf91mobiles
91mobiles recently conducted a Smart TV Buyer Insights Survey in which we asked over 3,000 respondents about the TV they own, aspects they look at on a new TV, and their TV buying preferences.
Software Delivery At the Speed of AI: Inflectra Invests In AI-Powered QualityInflectra
In this insightful webinar, Inflectra explores how artificial intelligence (AI) is transforming software development and testing. Discover how AI-powered tools are revolutionizing every stage of the software development lifecycle (SDLC), from design and prototyping to testing, deployment, and monitoring.
Learn about:
• The Future of Testing: How AI is shifting testing towards verification, analysis, and higher-level skills, while reducing repetitive tasks.
• Test Automation: How AI-powered test case generation, optimization, and self-healing tests are making testing more efficient and effective.
• Visual Testing: Explore the emerging capabilities of AI in visual testing and how it's set to revolutionize UI verification.
• Inflectra's AI Solutions: See demonstrations of Inflectra's cutting-edge AI tools like the ChatGPT plugin and Azure Open AI platform, designed to streamline your testing process.
Whether you're a developer, tester, or QA professional, this webinar will give you valuable insights into how AI is shaping the future of software delivery.
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024Tobias Schneck
As AI technology is pushing into IT I was wondering myself, as an “infrastructure container kubernetes guy”, how get this fancy AI technology get managed from an infrastructure operational view? Is it possible to apply our lovely cloud native principals as well? What benefit’s both technologies could bring to each other?
Let me take this questions and provide you a short journey through existing deployment models and use cases for AI software. On practical examples, we discuss what cloud/on-premise strategy we may need for applying it to our own infrastructure to get it to work from an enterprise perspective. I want to give an overview about infrastructure requirements and technologies, what could be beneficial or limiting your AI use cases in an enterprise environment. An interactive Demo will give you some insides, what approaches I got already working for real.
Slack (or Teams) Automation for Bonterra Impact Management (fka Social Soluti...Jeffrey Haguewood
Sidekick Solutions uses Bonterra Impact Management (fka Social Solutions Apricot) and automation solutions to integrate data for business workflows.
We believe integration and automation are essential to user experience and the promise of efficient work through technology. Automation is the critical ingredient to realizing that full vision. We develop integration products and services for Bonterra Case Management software to support the deployment of automations for a variety of use cases.
This video focuses on the notifications, alerts, and approval requests using Slack for Bonterra Impact Management. The solutions covered in this webinar can also be deployed for Microsoft Teams.
Interested in deploying notification automations for Bonterra Impact Management? Contact us at sales@sidekicksolutionsllc.com to discuss next steps.
Accelerate your Kubernetes clusters with Varnish CachingThijs Feryn
A presentation about the usage and availability of Varnish on Kubernetes. This talk explores the capabilities of Varnish caching and shows how to use the Varnish Helm chart to deploy it to Kubernetes.
This presentation was delivered at K8SUG Singapore. See https://feryn.eu/presentations/accelerate-your-kubernetes-clusters-with-varnish-caching-k8sug-singapore-28-2024 for more details.
The Art of the Pitch: WordPress Relationships and SalesLaura Byrne
Clients don’t know what they don’t know. What web solutions are right for them? How does WordPress come into the picture? How do you make sure you understand scope and timeline? What do you do if sometime changes?
All these questions and more will be explored as we talk about matching clients’ needs with what your agency offers without pulling teeth or pulling your hair out. Practical tips, and strategies for successful relationship building that leads to closing the deal.
The Art of the Pitch: WordPress Relationships and Sales
car number plate detection using matlab image & video processing
1. CAR NUMBER PLATE DETECTION USING
MATLAB IMAGE PROCESSING AND VIDEO
PROCESSING
PREPARED BY :
KESAVA KORUKONDA (546/14)
CHAUHAN MANIK RAO (553/14)
(GROUP NO.:- 7)
Guided by:
Shaima Qureshi
Co-guide
Nadeem
2. Introduction
Vehicle licence plate recognition involves identifying vehicle
by their licence plates.
It has become a task of prime importance with the increasing
In number of accident and traffic-rule violation.
A vehicle registration plate is metal are plastic plate
attached to a motor vehicle for official identification purpose
The registration number is a is numeric or an alpha numeric
code the unique identify the vehicle with in the issuing
regions database
3. Platform details
The platform we used here is MATLAB.
Matlab is a modern programming language environment.
The research work has been developed using the image
processing functionalities of the MATLAB platform.
The matlab version used here is ‘R2017b’ for developing
different modules.
MATLAB is used to solve technical computing problems
faster than traditional programming languages such as
C,C++ etc.
4. Project objective
• identification of stolen cars
• Smuggling of cars
• Invalid license plates
• Toll collection
• Application in authentication of car for the security purpose
5. Some important tasks
• Image capture
• Image pre-processing
• Character segmentation
• Character recognition
7. Work flow
Image was taken from real environment
Process digital images of license plates using existing techniques.
Techniques will perform alpha numeric conversions on the captured license
plate images into text entries.
System would check the extracted entries against a database in real time.
The entire system is implemented in MATLAB is used for detection and
recognition.
8. Pre-Processing
Pre-processing is very important for the good performance of character
segmentation.
Pre-processing consist of several stages.
• Resizing of an image.
• Rgb2gray.
• Median filtering.
• Dilation.
• Erosion.
• Morphological processing.
• Edge brightening.
• Thinning of image.
• Selection of region.
9. Character segmentation
Pre-processing Horizontal and vertical
segmentation
• In this stage we take the pre processed image as input
and we segment it by various methods.
• In this project we considered the bounding boxes
example by using connected components methods.
10. Horizontal and vertical segmentation
• Detect the horizontal lines in the image with a pixel
value of zero
• Converting the image into binary
• Use the simple “for loops” to detect the portions of the
image
• That had connected objects with a pixel value of ‘0’
and hence accordingly, the image was read.
13. Results
In the output we will be getting a result of characters of
the number plate in a notepad.
We can also create a database for the number plates
and can identify the plates/owner of the plates.
14. In case of video processing, we are dividing the
video into several number of frames.
In which we are choosing the best frames randomly
and we are processing the it as an image.
16. Conclusion & Future scope
1. The car number plate recognition using Matlab image
processing and video processing is presented . The
system use image processing techniques for the
identifying the vehicle from the database stored in the
computer . The system is implemented in Mat lab .
2. Can be improved to work for image taken at night time
3. Multiple matches & overlapping should be avoided.
4. Linking the video & image can be implemented by the
training method.
