License Plate Segmentation for Intelligent Transportation Systems

2003 ◽  
pp. 439-446 ◽  
Author(s):  
Muhammed Cinsdikici ◽  
Turhan Tunalı
Keyword(s):  
Intelligent Transportation Systems ◽  
Intelligent Transportation ◽  
Transportation Systems ◽  
License Plate

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

Quality indicator of the smart city transportation and logistics system

2020 ◽  
Vol 19 (11) ◽  
pp. 2116-2135
Author(s):  
G.V. Savin
Keyword(s):  
Intelligent Transportation Systems ◽  
Smart City ◽  
Urban Areas ◽  
Human Life ◽  
Life Quality ◽  
Intelligent Transportation ◽  
Transportation Systems ◽  
Logistics System ◽  
Organization And Management

Subject. The article considers functioning and development of process flows of transportation and logistics system of a smart city. Objectives. The study identifies factors and dependencies of the quality of human life on the organization and management of stream processes. Methods. I perform a comparative analysis of previous studies, taking into account the uniquely designed results, and the econometric analysis. Results. The study builds multiple regression models that are associated with stream processes, highlights interdependent indicators of temporary traffic and pollution that affect the indicator of life quality. However, the identified congestion indicator enables to predict the time spent in traffic jams per year for all participants of stream processes. Conclusions. The introduction of modern intelligent transportation systems as a component of the transportation and logistics system of a smart city does not fully solve the problems of congestion in cities at the current rate of urbanization and motorization. A viable solution is to develop cooperative and autonomous intelligent transportation systems based on the logistics approach. This will ensure control over congestion, the reduction of which will contribute to improving the life quality of people in urban areas.

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