scholarly journals Slant Correction of Vehicle License Plate Image

2005 ◽  
pp. 237-244 ◽  
Author(s):  
Lin Liu ◽  
Sanyuan Zhang ◽  
Yin Zhang ◽  
Xiuzi Ye
Keyword(s):  
License Plate

Iraqi Car License Plate Recognition Using OCR

2017 ◽  
Author(s):  
Safaa Omran ◽  
Jumana Jarallah
Keyword(s):  
License Plate ◽  
License Plate Recognition

License Plate Localization Using Novel Recursive Algorithm And Pixel Count Method

2013 ◽  
Vol 2 (2) ◽  
pp. 6-16 ◽  
Author(s):  
Siddharth Choubey ◽  
◽  
G.R. Sinha ◽  
Keyword(s):  
Recursive Algorithm ◽  
License Plate ◽  
Count Method

License plate location based on quaternion specific color-pair edge detection

2011 ◽  
Vol 31 (3) ◽  
pp. 729-732 ◽  
Author(s):  
Jian WANG ◽  
Li LIU ◽  
Tian-hui WANG
Keyword(s):  
Edge Detection ◽  
License Plate ◽  
License Plate Location ◽  
Color Pair ◽  
Plate Location

Double-Row License Plate Segmentation with Convolutional Neural Networks

2019 ◽  
Vol 31 (8) ◽  
pp. 1320 ◽  
Author(s):  
Hanli Zhao ◽  
Junru Liu ◽  
Lei Jiang ◽  
Jianbing Shen ◽  
Mingxiao Hu
Keyword(s):  
Neural Networks ◽  
Convolutional Neural Networks ◽  
License Plate ◽  
Double Row

Automatic Car Number Plate Recognition System for Authorization

2017 ◽  
Vol MCSP2017 (01) ◽  
pp. 30-34
Author(s):  
Somalin Sandha ◽  
Debaraj Rana
Keyword(s):  
Neural Network ◽  
Recognition System ◽  
Performance Level ◽  
License Plate ◽  
License Plate Recognition ◽  
Human Power ◽  
Automatic License Plate Recognition

In present day scenario the security and authentication is very much needed to make a safety world. Beside all security one vital issue is recognition of number plate from the car for Authorization. In the busy world everything cannot be monitor by a human, so automatic license plate recognition is one of the best application for authorization without involvement of human power. In the proposed method we have make the problem into three fold, firstly extraction of number plate region, secondly segmentation of character and finally Authorization through recognition and classification. For number plate extraction and segmentation we have used morphological based approaches where as for classification we have used Neural Network as classifier. The proposed method is working well in varieties of scenario and the performance level is quiet good.

scholarly journals Spatio-Temporal Visual Analysis for Urban Traffic Characters Based on Video Surveillance Camera Data

2021 ◽  
Vol 10 (3) ◽  
pp. 177
Author(s):  
Haochen Zou ◽  
Keyan Cao ◽  
Chong Jiang
Keyword(s):  
Video Surveillance ◽  
Traffic Management ◽  
Visual Analysis ◽  
Urban Traffic ◽  
License Plate ◽  
Road Vehicle ◽  
Urban Road ◽  
Surveillance Camera ◽  
Vehicle Density ◽  
Spatio Temporal

Urban road traffic spatio-temporal characters reflect how citizens move and how goods are transported, which is crucial for trip planning, traffic management, and urban design. Video surveillance camera plays an important role in intelligent transport systems (ITS) for recognizing license plate numbers. This paper proposes a spatio-temporal visualization method to discover urban road vehicle density, city-wide regional vehicle density, and hot routes using license plate number data recorded by video surveillance cameras. To improve the accuracy of the visualization effect, during data analysis and processing, this paper utilized Internet crawler technology and adopted an outlier detection algorithm based on the Dixon detection method. In the design of the visualization map, this paper established an urban road vehicle traffic index to intuitively and quantitatively reveal the traffic operation situation of the area. To verify the feasibility of the method, an experiment in Guiyang on data from road video surveillance camera system was conducted. Multiple urban traffic spatial and temporal characters are recognized concisely and efficiently from three visualization maps. The results show the satisfactory performance of the proposed framework in terms of visual analysis, which will facilitate traffic management and operation.

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