scholarly journals Vehicle License Plate Recognition

2021 ◽  
pp. 15-21
Author(s):  
Aman .. ◽  
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◽  
◽  
◽  
...  
Keyword(s):  
Intelligent Transportation Systems ◽  
Traffic Management ◽  
Recognition Rate ◽  
Intelligent Transportation ◽  
Transportation Systems ◽  
License Plate ◽  
License Plate Recognition ◽  
Single Class ◽  
Vehicle License Plate Recognition ◽  
Commercial Applications

One of the most significant parts of integrating computer technologies into intelligent transportation systems (ITS) is vehicle license plate recognition (VLPR). In most cases, however, to recognize a license plate successfully, the location of the license plate is to be determined first. Vehicle License Plate Recognition systems are used by law enforcement agencies, traffic management agencies, control agencies, and various government and non-government agencies. VLPR is used in various commercial applications, including electronic toll collecting, personal security, visitor management systems, parking management, and other corporate applications. As a result, calculating the correct positioning of a license plate from a vehicle image is an essential stage of a VLPR system, which substantially impacts the recognition rate and speed of the entire system. In the fields of intelligent transportation systems and image recognition, VLPR is a popular topic. In this research paper, we address the problem of license plate detection using a You Only Look Once (YOLO)-PyTorch deep learning architecture. In this research, we use YOLO version 5 to recognize a single class in an image dataset.

scholarly journals Automatic Vehicle License Plate Recognition Using Optimal K-Means With Convolutional Neural Network for Intelligent Transportation Systems

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 92907-92917 ◽  
Author(s):  
Irina Valeryevna Pustokhina ◽  
Denis Alexandrovich Pustokhin ◽  
Joel J. P. C. Rodrigues ◽  
Deepak Gupta ◽  
Ashish Khanna ◽  
...  
Keyword(s):  
Neural Network ◽  
Convolutional Neural Network ◽  
Intelligent Transportation Systems ◽  
Intelligent Transportation ◽  
Transportation Systems ◽  
License Plate ◽  
License Plate Recognition ◽  
Vehicle License Plate Recognition

Vehicle License Plate Recognition Based on Wavelet Transform and Vertical Edge Matching

2019 ◽  
Vol 34 (06) ◽  
pp. 2050016
Author(s):  
Zhongli Wang ◽  
Xiping Ma ◽  
Wenlin Huang
Keyword(s):  
Wavelet Transform ◽  
Road Traffic ◽  
Recognition Rate ◽  
Recognition Algorithm ◽  
License Plate ◽  
License Plate Recognition ◽  
Vertical Edge ◽  
Vertical Projection ◽  
Edge Matching ◽  
Vehicle License Plate Recognition

With the improvement of our country’s economic level and quality of life, the numbers and scales of highway networks and motor vehicles are constantly expanding, which makes the current road traffic burden more and more serious. As an important means of traffic automation management, license plate recognition (LPR) technology plays an important role in traffic surveillance and control. However, the recognition rate and accuracy of the traditional license plate recognition methods still need to be improved. In the case of poor surrounding environment, it is prone to localization failure, vehicle license plate recognition errors or unrecognizable phenomena. Wavelet transform, as another landmark signal processing method after Fourier transform, has been widely used in the field of image processing. In China, the number of horizontal lines is usually larger than that of vertical lines. If the two vertical boundaries of the license plate can be detected successfully, the four angles of the license plate can be determined efficiently to complete the license plate positioning. In view of the advantages of wavelet transform technology and the characteristics of vehicle license plate, in this paper, a vehicle license plate recognition algorithm based on wavelet transform and vertical edge matching is proposed. The edge of the license plate is detected by wavelet transform technology, and then the license plate is located by vertical edge matching technology. After the location is realized, the characters are segmented by vertical projection method and the characters are recognized by improved BP neural network algorithm. The experimental results show that the proposed vehicle license plate recognition algorithm based on wavelet transform and vertical edge matching performs well in algorithm performance, which provides a good reference for the development of vehicle license plate recognition system.

scholarly journals Visualizing the Intellectual Structure and Evolution of Intelligent Transportation Systems: A Systematic Analysis of Research Themes and Trends

2020 ◽  
Vol 12 (21) ◽  
pp. 8759 ◽  
Author(s):  
Nadia Karina Gamboa-Rosales ◽  
José María Celaya-Padilla ◽  
Ana Luisa Hernandez-Gutierrez ◽  
Arturo Moreno-Baez ◽  
Carlos E. Galván-Tejada ◽  
...  
Keyword(s):  
Intelligent Transportation Systems ◽  
Traffic Management ◽  
Intelligent Transportation ◽  
Transportation Systems ◽  
Intellectual Structure ◽  
Structure Evolution ◽  
Future Research ◽  
Systematic Analysis ◽  
Main Research ◽  
Research Themes

According to the United Nations, 70% of the world’s population will live in cities by 2050. This growth will be reflected in the demand for better services that should be adjusted to the collective and individual needs of the population. Governments and organizations are working on defining and implementing strategies that will enable them to respond to these challenges. The main challenges are related to transport and its management, considering transportation as a core issue in the economy, sustainability, and development of the regions. In this way, the Intelligent Transportation Systems (ITS) play a key role in the response to these scenarios, being that they are the framework where the new hardware and software tools are integrated, allowing an efficient development of transportation systems management, attending to aspects such as: traffic management, communications between vehicles and infrastructures, and security, among others. Nevertheless, the concept of ITS evolves rapidly so it is necessary to understand its evolution. To do that, the current research develops a thematic analysis of ITS in literature, evaluating the intellectual structure and its evolution using SciMAT, quantifying the main bibliometric performance indicators, and identifying the main research areas, authors, journals, and countries. To this purpose, the publications related to ITS from 1993 to 2019 available in the Web of Science (WoS) Core Collection were retrieved (7649 publications) and analyzed. Finally, one of the main results is the latest research themes map of ITS, considering its intellectual structure, evolution, and relationship. It assists in the definition and implementation of strategies, the identification of the scientific, academic, and business opportunities, and future research lines to consolidate the role of ITS in the new city models.

Guidelines for Application of Portable Work Zone Intelligent Transportation Systems

2003 ◽  
Vol 1824 (1) ◽  
pp. 15-22 ◽  
Author(s):  
Michael D. Fontaine
Keyword(s):  
Intelligent Transportation Systems ◽  
Traffic Management ◽  
Intelligent Transportation ◽  
Transportation Systems ◽  
Lessons Learned ◽  
Work Zone ◽  
Expected Performance ◽  
Operational Tests ◽  
Message Signs ◽  
Alternate Routes

Work zone intelligent transportation systems (WZITSs) are promoted as a way to improve safety and reduce congestion at work zone locations where traditional traffic management centers do not exist. These systems usually integrate portable changeable message signs and speed sensors with a central control system that automatically determines appropriate messages that are based on current traffic conditions. Manufacturers of these systems claim that WZITSs can warn drivers of downstream congestion, alert drivers to slower speeds ahead, and suggest alternate routes on the basis of prevailing conditions. Transportation agencies are often asked to make decisions on the installation of a WZITS without the benefit of objective information on its expected performance. Relatively few operational tests of these systems have been performed, and the results are not always well documented or conclusive. Agencies need guidance to help them determine whether a WZITS system would improve safety and operations at a specific site. Applications of WZITSs are reviewed, and a series of guidelines for their deployment, based on lessons learned from past tests, is presented.

Navigation and Intelligent Transportation Systems

1998 ◽  
Keyword(s):  
Traffic Safety ◽  
Intelligent Transportation Systems ◽  
Traffic Management ◽  
Cellular Phone ◽  
Intelligent Transportation ◽  
Transportation Systems ◽  
Navigation Systems ◽  
Route Guidance ◽  
Highway Traffic ◽  
National Highway Traffic Safety

Navigation and Intelligent Transportation Systems contains 40 papers covering the technical and functional aspects of these systems including: 3D mapping, route guidance, cellular phone access, electronic compasses, and the history and future of navigation systems. The book also covers the important role of navigation in Intelligent Transportation Systems concerned with traffic management, traveler information, vehicle control systems, commercial vehicle operations, and public and rural transportation systems. The book concludes with a chapter on the Intelligent Vehicle Initiative, a joint program between the National Highway Traffic Safety Administration, the Federal Highway Administration, and the Federal Transit Administration.

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