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.
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.
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.
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.
Traffic Violation Detector using Object Detection that helps to detects the vehicle number plate that is violating traffic rules and by that number the admin finds the details of the car owner and send a penalty charge sheet to the owner home.
Number plate identification perimeter protection system. Control which vehicle access your premise. Assign rules for vehicles trying to enter the premise. Blacklist vehicles. Generate Alert if a blacklisted or unregistered vehicle trying to enter the area. Make efficient use of your security staff
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.
Advanced driver assistance systems are designed to increase car safety more generally road safety.
Basically Advanced driver assists(ADS) systems helps the driver in the driving process and enables safe, relaxed driving. It makes sense to get your new car with driver assist features if you find it at a reasonable price as it helps you drive easily and safely in everyday use.
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.
Traffic Violation Detector using Object Detection that helps to detects the vehicle number plate that is violating traffic rules and by that number the admin finds the details of the car owner and send a penalty charge sheet to the owner home.
Number plate identification perimeter protection system. Control which vehicle access your premise. Assign rules for vehicles trying to enter the premise. Blacklist vehicles. Generate Alert if a blacklisted or unregistered vehicle trying to enter the area. Make efficient use of your security staff
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.
Advanced driver assistance systems are designed to increase car safety more generally road safety.
Basically Advanced driver assists(ADS) systems helps the driver in the driving process and enables safe, relaxed driving. It makes sense to get your new car with driver assist features if you find it at a reasonable price as it helps you drive easily and safely in everyday use.
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.
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.
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.
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.
A License plate is a rectangular plate which is alphanumeric. The license plate is fixed on the vehicle and used to identify the
vehicle along with honor of that vehicle. There is a huge nos. of vehicles are on the road word wile so that traffic control and
vehicle owner identification has become a major problem.
The automatic number plate reorganization (ANPR) is one of the solutions of such kind of problem. There is nos. of methodologies
but it is challenging task as some of the factors like high speed of vehicles, languages of number plate & mostly non-uniform
letter on number plate effects a lot in recognition. The license plate recognition (LPR) system have many application like payment
of parking fees; toll fee on highway; traffic monitoring system; border security system; signal system etc.
In this paper, the different method of license plate recognition is discussed. The systems first detects the vehicle and capture the
image then the number plate of vehicle is extracted from the image using image Segmentation optical character recognition technique
is used for the character recognition. Then the resulting date is compared with the database record so we come up the information
like the vehicle’s owner, vehicle registration place, address etc. it is observed that developed system successfully defect
& recognize the vehicle number plate on real image.
Explore our comprehensive data analysis project presentation on predicting product ad campaign performance. Learn how data-driven insights can optimize your marketing strategies and enhance campaign effectiveness. Perfect for professionals and students looking to understand the power of data analysis in advertising. for more details visit: https://bostoninstituteofanalytics.org/data-science-and-artificial-intelligence/
Chatty Kathy - UNC Bootcamp Final Project Presentation - Final Version - 5.23...John Andrews
SlideShare Description for "Chatty Kathy - UNC Bootcamp Final Project Presentation"
Title: Chatty Kathy: Enhancing Physical Activity Among Older Adults
Description:
Discover how Chatty Kathy, an innovative project developed at the UNC Bootcamp, aims to tackle the challenge of low physical activity among older adults. Our AI-driven solution uses peer interaction to boost and sustain exercise levels, significantly improving health outcomes. This presentation covers our problem statement, the rationale behind Chatty Kathy, synthetic data and persona creation, model performance metrics, a visual demonstration of the project, and potential future developments. Join us for an insightful Q&A session to explore the potential of this groundbreaking project.
Project Team: Jay Requarth, Jana Avery, John Andrews, Dr. Dick Davis II, Nee Buntoum, Nam Yeongjin & Mat Nicholas
Opendatabay - Open Data Marketplace.pptxOpendatabay
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2. Number Plate Recognition
Number Plate Recognition (NPR) is a computer vision-based
technology in which we capture the image of vehicle . After
capturing the image of the vehicle we extract the number
plate of a vehicle to identify the details of the owner of the
vehicle. This project aims to design an efficient automatic
authorized vehicle identification system by using the vehicle
number plate.
3. Requirements : -
Hardware Requirements :-
1) Camera
2) Computer
3) Infra Red Detector (for night images)
4) GPU (graphical Processing Unit)
Software Requirements :-
1) Number plate recognition software
2) Database
3) A backend system for provide the details of number of Car
4. Working : -
Working of this system can be break down in five steps which are
follows : -
1) Capturing of image from camera
2) Pre processing of image
3) Number plate detection from image (using YOLO)
4) Character recognition from plate
5) Output of character to the Database
5. Capturing and Preprocessing of the image
At first we capture the image of the vehicle from the camera and store it
into the PC. After Capturing of the image we first detect the car in the
image if there is any car present in the image than we will pass it to the
further model otherwise it will neglect the photo. If there is car in the
image than we first remove the background of the car for this we can use
any of pre trained API like (remove.bg) for removing the background of
the image and adjust the light exposure in the image . After this we pass
the image to the plate detection model.
6. Number plate detection and character
Recognition
Now as the image is passed to plate detector. Here in plate detector we
use machine learning model YOLO to detect the number plate in the
image. After this we pass the detected plate to the Optical Character
Recognition system where it will detect the character from the image
and provide the number plate of the car as a string to the Database
7. Database
As now we get the number of the car So now we can pass this to a API which will
provide all the details of the car like owner name of vehicle, model of the vehicle.
After getting all the details of the vehicle it will store these details in a entry
Database of the place So that it can be use in further time at the requirement.
8. Similar solution
1.RFID(Radio Frequency Identification):- This technology could be a variety of wireless
communication during which we have a tendency to use magnetic or electric coupling within the
frequency portion of the spectrum to unambiguously establish an individual or object.
This is a system that has primarily 2 components:1. Tags and 2.Readers.
2.DSRC(Dedicated Short Range Communication) :-This technology is based on bidirectional data
transfer radio communication between fixed gadgets which are Installed at roadside and vehicles.
3.There are some other technologies used like GNSS which determine geophysical position of a
vehicle, distance travelled on specific road for road charges and other information.
9. Outcome and Benefit of the Project
Outcome of this proposal-
1) Save time
2) Errors reduction
3) Ease in tracking the criminals
This model can be used at following places : -
1) Automatically open a gate or barrier into a secured area for authorised
members
2) Helping in finding the stolen vehicle
3) Traffic flow management.
10. Future Scope : -
1) The number plate recognition system can be enhanced to record all types of
number plates whatever their size and font type may be.
2) The woking of this model can be made faster as the technique which are
implemented at this time are slow they usually take around 2 second to provide
complete result .
3) Could detect the fake Number plate and take the image of the driver and store it
in the Database.
4) Could detect the vehicle which run fast if they are breaking the traffic rules than
we could put fine on the vehicle driver.
11. Conclusion
By number plate recognition system management, storage and sharing of
vehicle data becomes very easy and fast.
It will shorten the vehicle entry and exit time thereby hastening the process
of parking.
This system will give instant additional information about the vehicle as the
database will also contain vehicle RC information i.e registration record from
the government agencies.