Home / Advanced Search

  • Title/Keywords

  • Author/Affliations

  • Journal

  • Article Type

  • Start Year

  • End Year

Update SearchingClear
  • Articles
  • Online
Search Results (9)
  • Open Access


    YOLO and Blockchain Technology Applied to Intelligent Transportation License Plate Character Recognition for Security

    Fares Alharbi1, Reem Alshahrani2, Mohammed Zakariah3,*, Amjad Aldweesh1, Abdulrahman Abdullah Alghamdi1

    CMC-Computers, Materials & Continua, Vol.77, No.3, pp. 3697-3722, 2023, DOI:10.32604/cmc.2023.040086

    Abstract Privacy and trust are significant issues in intelligent transportation systems (ITS). Data security is critical in ITS systems since sensitive user data is communicated to another user over the internet through wireless devices and routes such as radio channels, optical fiber, and blockchain technology. The Internet of Things (IoT) is a network of connected, interconnected gadgets. Privacy issues occasionally arise due to the amount of data generated. However, they have been primarily addressed by blockchain and smart contract technology. While there are still security issues with smart contracts, primarily due to the complexity of writing… More >

  • Open Access


    License Plate Recognition via Attention Mechanism

    Longjuan Wang1,2, Chunjie Cao1,2, Binghui Zou1,2, Jun Ye1,2,*, Jin Zhang3

    CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1801-1814, 2023, DOI:10.32604/cmc.2023.032785

    Abstract License plate recognition technology use widely in intelligent traffic management and control. Researchers have been committed to improving the speed and accuracy of license plate recognition for nearly 30 years. This paper is the first to propose combining the attention mechanism with YOLO-v5 and LPRnet to construct a new license plate recognition model (LPR-CBAM-Net). Through the attention mechanism CBAM (Convolutional Block Attention Module), the importance of different feature channels in license plate recognition can be re-calibrated to obtain proper attention to features. Force information to achieve the purpose of improving recognition speed and accuracy. Experimental More >

  • Open Access


    Deep Learning and SVM-Based Approach for Indian Licence Plate Character Recognition

    Nitin Sharma1, Mohd Anul Haq2, Pawan Kumar Dahiya3, B. R. Marwah4, Reema Lalit5, Nitin Mittal6, Ismail Keshta7,*

    CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 881-895, 2023, DOI:10.32604/cmc.2023.027899

    Abstract Every developing country relies on transportation, and there has been an exponential expansion in the development of various sorts of vehicles with various configurations, which is a major component strengthening the automobile sector. India is a developing country with increasing road traffic, which has resulted in challenges such as increased road accidents and traffic oversight issues. In the lack of a parametric technique for accurate vehicle recognition, which is a major worry in terms of reliability, high traffic density also leads to mayhem at checkpoints and toll plazas. A system that combines an intelligent domain… More >

  • Open Access


    Hybrid Metaheuristics Based License Plate Character Recognition in Smart City

    Esam A. AlQaralleh1, Fahad Aldhaban2, Halah Nasseif2, Bassam A.Y. Alqaralleh2,*, Tamer AbuKhalil3

    CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 5727-5740, 2022, DOI:10.32604/cmc.2022.026780

    Abstract Recent technological advancements have been used to improve the quality of living in smart cities. At the same time, automated detection of vehicles can be utilized to reduce crime rate and improve public security. On the other hand, the automatic identification of vehicle license plate (LP) character becomes an essential process to recognize vehicles in real time scenarios, which can be achieved by the exploitation of optimal deep learning (DL) approaches. In this article, a novel hybrid metaheuristic optimization based deep learning model for automated license plate character recognition (HMODL-ALPCR) technique has been presented for… More >

  • Open Access


    Automatic License Plate Recognition System for Vehicles Using a CNN

    Parneet Kaur1, Yogesh Kumar1, Shakeel Ahmed2,*, Abdulaziz Alhumam2, Ruchi Singla3, Muhammad Fazal Ijaz4

    CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 35-50, 2022, DOI:10.32604/cmc.2022.017681

    Abstract Automatic License Plate Recognition (ALPR) systems are important in Intelligent Transportation Services (ITS) as they help ensure effective law enforcement and security. These systems play a significant role in border surveillance, ensuring safeguards, and handling vehicle-related crime. The most effective approach for implementing ALPR systems utilizes deep learning via a convolutional neural network (CNN). A CNN works on an input image by assigning significance to various features of the image and differentiating them from each other. CNNs are popular for license plate character recognition. However, little has been reported on the results of these systems with More >

  • Open Access


    Deep Learning Based License Plate Number Recognition for Smart Cities

    T. Vetriselvi1, E. Laxmi Lydia2, Sachi Nandan Mohanty3,4, Eatedal Alabdulkreem5, Shaha Al-Otaibi6, Amal Al-Rasheed6, Romany F. Mansour7,*

    CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 2049-2064, 2022, DOI:10.32604/cmc.2022.020110

    Abstract Smart city-aspiring urban areas should have a number of necessary elements in place to achieve the intended objective. Precise controlling and management of traffic conditions, increased safety and surveillance, and enhanced incident avoidance and management should be top priorities in smart city management. At the same time, Vehicle License Plate Number Recognition (VLPNR) has become a hot research topic, owing to several real-time applications like automated toll fee processing, traffic law enforcement, private space access control, and road traffic surveillance. Automated VLPNR is a computer vision-based technique which is employed in the recognition of automobiles… More >

  • Open Access


    Automatic Vehicle License Plate Recognition Using Optimal Deep Learning Model

    Thavavel Vaiyapuri1, Sachi Nandan Mohanty2, M. Sivaram3, Irina V. Pustokhina4, Denis A. Pustokhin5, K. Shankar6,*

    CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 1881-1897, 2021, DOI:10.32604/cmc.2021.014924

    Abstract The latest advancements in highway research domain and increase inthe number of vehicles everyday led to wider exposure and attention towards the development of efficient Intelligent Transportation System (ITS). One of the popular research areas i.e., Vehicle License Plate Recognition (VLPR) aims at determining the characters that exist in the license plate of the vehicles. The VLPR process is a difficult one due to the differences in viewpoint, shapes, colors, patterns, and non-uniform illumination at the time of capturing images. The current study develops a robust Deep Learning (DL)-based VLPR model using Squirrel Search Algorithm… More >

  • Open Access


    Vehicle License Plate Recognition System Based on Deep Learning in Natural Scene

    Ze Chen, Leiming Yan*, Siran Yin, Yuanmin Shi

    Journal on Artificial Intelligence, Vol.2, No.4, pp. 167-175, 2020, DOI:10.32604/jai.2020.012716

    Abstract With the popularity of intelligent transportation system, license plate recognition system has been widely used in the management of vehicles in and out of closed communities. But in the natural environment such as video monitoring, the performance and accuracy of recognition are not ideal. In this paper, the improved Alex net convolution neural network is used to remove the false license plate in a large range of suspected license plate areas, and then the projection transformation and Hough transformation are used to correct the inclined license plate, so as to build an efficient license plate More >

  • Open Access


    Adversarial Attacks on License Plate Recognition Systems

    Zhaoquan Gu1, Yu Su1, Chenwei Liu1, Yinyu Lyu1, Yunxiang Jian1, Hao Li2, Zhen Cao3, Le Wang1, *

    CMC-Computers, Materials & Continua, Vol.65, No.2, pp. 1437-1452, 2020, DOI:10.32604/cmc.2020.011834

    Abstract The license plate recognition system (LPRS) has been widely adopted in daily life due to its efficiency and high accuracy. Deep neural networks are commonly used in the LPRS to improve the recognition accuracy. However, researchers have found that deep neural networks have their own security problems that may lead to unexpected results. Specifically, they can be easily attacked by the adversarial examples that are generated by adding small perturbations to the original images, resulting in incorrect license plate recognition. There are some classic methods to generate adversarial examples, but they cannot be adopted on More >

Displaying 1-10 on page 1 of 9. Per Page