scholarly journals Vehicle license plate recognition for fog‐haze environments

2020 ◽  
Author(s):  
Xianli Jin ◽  
Ruocong Tang ◽  
Linfeng Liu ◽  
Jiagao Wu
Keyword(s):  
License Plate ◽  
License Plate Recognition ◽  
Vehicle License Plate Recognition

Application of Image Processing to the Vehicle License Plate Recognition

2013 ◽  
Vol 760-762 ◽  
pp. 1638-1641 ◽  
Author(s):  
Chun Yu Chen ◽  
Bao Zhi Cheng ◽  
Xin Chen ◽  
Fu Cheng Wang ◽  
Chen Zhang
Keyword(s):  
Traffic Engineering ◽  
Character Recognition ◽  
Character Segmentation ◽  
License Plate ◽  
License Plate Recognition ◽  
Edge Extraction ◽  
Recognition Method ◽  
License Plate Location ◽  
Vehicle License Plate Recognition ◽  
Plate Location

At present, the traffic engineering and automation have developed, and the vehicle license plate recognition technology need get a corresponding improvement also. In case of identifying a car license picture, the principle of automatic license plate recognition is illustrated in this paper, and the processing is described in detail which includes the pre-processing, the edge extraction, the license plate location, the character segmentation, the character recognition. The program implementing recognition is edited by Matlab. The example result shows that the recognition method is feasible, and it can be put into practice.

scholarly journals The fast recognition of vehicle license plate based on the improved template matching

2018 ◽  
Vol 176 ◽  
pp. 01029 ◽  
Author(s):  
Zhixin Jiang ◽  
Zhengkui Lin ◽  
Jing Tang ◽  
Hao Li ◽  
You Menglu
Keyword(s):  
Fuzzy Number ◽  
Template Matching ◽  
Real System ◽  
License Plate ◽  
License Plate Recognition ◽  
Slow Speed ◽  
Recognition Time ◽  
Fast Recognition ◽  
Vehicle License Plate Recognition

In order to solve the problem of low accuracy and slow speed in vehicle license plate recognition, a method of number-plate recognition using template matching is proposed. It can effectively recognize low quality and fuzzy number-plate image in real system .The accuracy is 95%, and the recognition time is close to 0.14s.

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.

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