International Research Journal of Engineering and Technology (IRJET)
e-ISSN: 2395-0056
Volume: 09 Issue: 11 | Nov 2022
p-ISSN: 2395-0072
www.irjet.net
Raspberry Pi Vehicles Number Plate Recognition Ms Snehal Ashtekar1, Ms Ishita Kanu2, Mr Bhavya Shah3, Dr. Jyoti Mali4 1234Department
of EXTC, Atharva College of Engineering, Maharashtra, India -----------------------------------------------------------------------***------------------------------------------------------------------Abstract- The project's goal is to use a Raspberry Pi to 2. LITERATURE SURVEY:automatically take a photo with the webcam while also identifying a passing car's license plate. Vehicle number plate recognition is a difficult but essential system. This is very beneficial for automating toll booths, automatic signal breaker identification locating traffic law infractions, and insurance checks.
This paper proposed the Electronic Toll Collection System based on RFID which has the advantages of less cost, small size, and high reliability. It is very suitable for practical applications with the rapid development of the national economy, the total mileage of expressways and vehicle population remain constantly increasing in china, accordingly, the expressway network has become more complex [1].
Key Words:
Raspberry pi, Number plate, Optical Character Recognition, Character Segmentation, Image Segmentation.
1.
This paper proposed that, the double chance algorithm as an approach to car license plate extraction. The first algorithm extracts the line segments and groups them based on a set of geometrical conditions, using a real-life database collected by a speed enforcement camera, they obtained a high success rate of 99.5%, through a double chance approach with verification [2].
Introduction:-
Even though difficult, vehicle number plate recognition is an essential system. Automating toll booths, identifying signal breakers automatically, and identifying traffic law violators all benefit greatly from this.
This paper proposed a method to detect Korean vehicle plates from black box videos. It works in two stages: The first stage aims to locate a set of candidate plate regions and the second stage identifies only actual plates from candidates by using a support vector machine classifier. Internet services that share vehicle Black Box videos need a way to obfuscate license plates in the uploaded video because of privacy issues [3].
Here, we propose an automatic license plate recognition system for the Raspberry Pi that makes use of image processing. The system uses a Raspberry Pi, an LCD circuit, and a camera. The system continuously looks for any signs of number plates in the incoming camera footage. The camera processes the camera input and eliminates the number plate portion of the image when it detects a number plate in front of it. uses OCR to separate the license plate number from the extracted image. The system then shows the extracted number on an LCD. So, using a Raspberry Pi, we propose a fully functional system for reading license plates.
The objective of this paper is to complete an automatic recognition system using OCR, they have used the existing closed circuit, television, or road rule for informant cameras or ones specifically designed for the task. The images of a vehicle's license plate are captured and processed by segmentation of character and are verified by the Raspberry pi processor authentication proposed [4].
This fully automated number plate recognition system employs image processing to find the number plate, which is then used for additional analysis. Digital image processing methods are used by this automatic system. This initiative aims to intelligently collect insurance and fines. In some nations, we have automated systems for collecting fines and insurance, but they are all expensive fixes, so in this country, we have put in place a budgetfriendly monitoring system. a system for automatically identifying license plates. Following is a summary of the procedure. This instantly finds, identifies, and recognizes a license plate. After being captured, the image is processed using image processing methods. The detected license plate is also used to send emails, check fines, and fulfill other insurance and legal requirements.
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The system aims at the designing system which captures the image of the vehicle number plate and these details were used by the Raspberry pi processor for authentication. The system also alerts the authorities when any unauthorized image of a number plate is detected using the buzzer alarm system. In this situation, LED indicators may even be used to signal number plate recognition. The camera records the number plate image whenever a vehicle passes by the system. The image of number plate details is fed as input to the Raspberry pi processor. The main objective of this paper is to provide researchers with an analytical inspection of Automatic License Plate Recognition research by assorting the
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