Automated parking management system for identifying vehicle number plate

<p>By using image processing, the Automated parking management system (APMS) to recognize the license plate number for efficient management of vehicle parking and vehicle billing. It is an independent real-time system, reduces number of people involvement in parking areas. The main aim of this system is to automated payment collection. This (APMS) system extract and recognize license plate numbers from the vehicles, then that image is being processed and used to generate an electronic bill. Generally in the parking lots heavy labor work is needed. This system used to decrease the cost of the labor and also enhance the performance of the APMS. This system is composed of vehicles license plate number extraction, character segmentation and character recognition. A proper pre-processing is done before extracting the license plate and it also generates the entry time and exit time of the vehicle and finally generates the electronic bill.</p>

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Intelligent Parking System

International Journal of Recent Technology and Engineering - 2 ◽

10.35940/ijrte.b1100.0782s319 ◽

2019 ◽

Vol 8 (2S3) ◽

pp. 550-553

Keyword(s):

Urban Communities ◽

Character Recognition ◽

Optical Character Recognition ◽

Exit Time ◽

Region Of Interest ◽

License Plate ◽

Past Study ◽

Entry Time ◽

Parking System ◽

Best Fit

As a key part of Automated vehicle technology Intelligent Parking System has become a popular research topic. Intelligent Parking System can grant permission to access the parking area with less human inference. This system can capture image of the vehicle, identify the type of vehicle and allot best fit and optimal parking slot based on its size. It extracts the vehicle’s License plate number, entry time, exit time and calculate total time of the vehicle present with in the parking space. Here, sensors are utilized to identify the presence of the vehicle during entry and exit. Two cameras are utilized to extract features. One camera is used to identify the Region of Interest, Vehicle license plate and identify the characters from the license plate. Tesseract Engine and Optical Character Recognition (OCR) functions are used to detect characters from the image. Another camera is utilized to extract features like dimensions of the vehicle using machine learning operations such as Convolutional Neural Network (CNN). Based on the size of the vehicle, best fit parking slot is allotted which gives optimal usage of parking area. These days the quantity of vehicles is expanding exceptionally, so that, searching for an empty parking slot turns out to be increasingly troublesome. By installing the Intelligent Parking System, in places like, shopping malls, train stations, and airports the need for searching of parking slot significantly reduces. A past study has demonstrated that traffic because of vehicle’s parking slot searching in downtowns of significant urban communities can represent half of the absolute traffic. With such a hefty traffic jam and time delay in parking slot identifying, Intelligent Parking System will be in great demand

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Character Recognition of License Plate Number Using Convolutional Neural Network

Lecture Notes in Computer Science - Visual Informatics: Sustaining Research and Innovations ◽

10.1007/978-3-642-25191-7_6 ◽

2011 ◽

pp. 45-55 ◽

Cited By ~ 12

Author(s):

Syafeeza Ahmad Radzi ◽

Mohamed Khalil-Hani

Keyword(s):

Neural Network ◽

Convolutional Neural Network ◽

Character Recognition ◽

License Plate ◽

Plate Number

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BP-Neural Network for Plate Number Recognition

International Journal of Digital Crime and Forensics ◽

10.4018/ijdcf.2016070103 ◽

2016 ◽

Vol 8 (3) ◽

pp. 34-45 ◽

Cited By ~ 3

Author(s):

Jia Wang ◽

Wei Qi Yan

Keyword(s):

Neural Network ◽

Character Recognition ◽

Back Propagation ◽

License Plate ◽

License Plate Recognition ◽

Traffic Surveillance ◽

Plate Number ◽

Number Recognition ◽

Traffic Systems ◽

Artificial Neural Network Ann

The License Plate Recognition (LPR) as one crucial part of intelligent traffic systems has been broadly investigated since the boosting of computer vision techniques. The motivation of this paper is to probe in plate number recognition which is an important part of traffic surveillance events. In this paper, locating the number plate is based on edge detection and recognizing the plate numbers is worked on Back-Propagation (BP) Artificial Neural Network (ANN). Furthermore, the authors introduce the system implementation and take advantage of the well-known Matlab platform to delve how to accurately recognize plate numbers. There are 80 samples adopted to test and verify the proposed plate number recognition method. The experimental results demonstrate that the accuracy of the authors' character recognition is above 70%.

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Vehicle images reconstruction using SRCNN for improving the recognition accuracy of vehicle license plate number

Jurnal Teknologi dan Sistem Komputer ◽

10.14710/jtsiskom.2020.13726 ◽

2020 ◽

Vol 8 (4) ◽

pp. 304-310

Author(s):

Windra Swastika ◽

Ekky Rino Fajar Sakti ◽

Mochamad Subianto

Keyword(s):

High Resolution ◽

Character Recognition ◽

Recognition Accuracy ◽

Super Resolution ◽

Training Data ◽

License Plate ◽

Plate Number ◽

Average Accuracy ◽

Number Recognition ◽

High Resolution Images

Low-resolution images can be reconstructed into high-resolution images using the Super-resolution Convolution Neural Network (SRCNN) algorithm. This study aims to improve the vehicle license plate number's recognition accuracy by generating a high-resolution vehicle image using the SRCNN. The recognition is carried out by two types of character recognition methods: Tesseract OCR and SPNet. The training data for SRCNN uses the DIV2K dataset consisting of 900 images, while the training data for character recognition uses the Chars74 dataset. The high-resolution images constructed using SRCNN can increase the average accuracy of vehicle license plate number recognition by 16.9 % using Tesseract and 13.8 % with SPNet.

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A Low-Cost On-Street Parking Management System Based on Bluetooth Beacons

Sensors ◽

10.3390/s20164559 ◽

2020 ◽

Vol 20 (16) ◽

pp. 4559 ◽

Cited By ~ 1

Author(s):

Chi-Fang Chien ◽

Hui-Tzu Chen ◽

Chi-Yi Lin

Keyword(s):

Management System ◽

Low Cost ◽

Distance Estimation ◽

Magnetic Sensors ◽

License Plate ◽

City Governments ◽

Human Labor ◽

Parking Management ◽

Information And Communication ◽

Smart Parking

In recent years, many city governments around the world have begun to use information and communication technology to increase the management efficiency of on-street parking. Among various experimental smart parking projects, deployment of wireless magnetic sensors and smart parking meters are quite common. However, using wireless magnetic sensors can only detect the occupancy of parking spaces without the knowledge of who are currently using these parking spaces; human labor is still needed to issue the parking bills. In contrast, smart parking meters based on image recognition can detect the occupancy of parking spaces along with the license plate numbers, but the cost of deploying smart parking meters is relatively high. In this research, we investigate the feasibility of building an on-street parking management system mainly based on low-cost Bluetooth beacons. Specifically, beacon transmitters are installed in the vehicles, and beacon receivers are deployed along the roadside parking spaces. By processing the received beacon signals using Kalman filter, our system can detect the occupancy of parking spaces as well as the identification of the vehicles. Although distance estimation using the received signal strength is not accurate, our experiments show that it suffices for correct detection of parking occupancy.

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Design of Improved UI of Automatic Parking Management System using License Plate Recognition

Journal of the Korea Academia-Industrial cooperation Society ◽

10.5762/kais.2014.15.2.1083 ◽

2014 ◽

Vol 15 (2) ◽

pp. 1083-1088

Author(s):

Bong-Gi Kim

Keyword(s):

Management System ◽

License Plate ◽

License Plate Recognition ◽

Parking Management ◽

Automatic Parking

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Vehicle Number Plate Recognition using Micro Processor

International Journal of Innovative Technology and Exploring Engineering - Special Issue ◽

10.35940/ijitee.l2642.1081219 ◽

2019 ◽

Vol 8 (12) ◽

pp. 3682-3684

Keyword(s):

Image Processing ◽

Character Recognition ◽

Optical Character Recognition ◽

Recognition System ◽

Processing Technology ◽

License Plate ◽

Text Format ◽

Optical Character ◽

Plate Number ◽

Image Processing Technology

An automatic license number plate recognition system that uses image processing technology for identifying the written characters and numbers on the vehicle’ license plate. The system can be used in highly secured areas to provide more safety, and can be used in parking, traffic, and other places to monitor all vehicle’s number plate in a predefined area. The character is recognized by the OCR technology that is optical character recognition system. It generates the vehicle’s license plate number in a text format. The recognized number from the license plate then can be used to retrieve more information about the vehicle and the owner.

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