Study of License Plate Recognition Technology

2013 ◽  
Vol 834-836 ◽  
pp. 1035-1038 ◽  
Author(s):  
Shuai Yuan ◽  
Guo Yun Zhang ◽  
Jian Hui Wu ◽  
Long Yuan Guo

License plate recognition technology has been widely used with the development of intelligent traffic system, which studies vehicle identification based on digital image processing technology. This paper presents system design and realization of recognition system for license plate. License plate image is preprocessed by gradation and binaryzation at first, then the image noise caused by dirt is filtered by a mean value method. We adopt horizontal and vertical projection method to locate license plate. Character segmentation and recognition are carried out at last. Test result shows that the method presented has good accuracy, quick speed and strong robustness for realtime application.

2010 ◽  
Vol 44-47 ◽  
pp. 3667-3671
Author(s):  
Zhen Ma ◽  
Jian Lei Li ◽  
Xue Fei Tan

With the growth in number of vehicle, intelligent vehicle management has become the research hotspot, and license plate automatic recognition system is also of great concern as a important technology of intelligent traffic system. In this paper, Hough transform used to edge extraction, tilt correction algorithm and character recognition based on Haursdorff distance are discussed. At last, the license plate recognition system is designed and implemented, and then the experimental result is analyzed.


Author(s):  
Weifang Zhai ◽  
Terry Gao ◽  
Juan Feng

The license plate recognition technology is an important part of the construction of an intelligent traffic management system. This paper mainly researches the image preprocessing, license plate location, and character segmentation in the license plate recognition system. In the preprocessing part of the image, the edge detection method based on convolutional neural network (CNN) is used for edge detection. In the design of the license plate location, this paper proposes a location method based on a combination of mathematical morphology and statistical jump points. First, the license plate area is initially located using mathematical morphology-related operations and then the location of the license plate is accurately located using statistical jump points. Finally, the plate with tilt is corrected. In the process of character segmentation, the border and delimiter are first removed, then the character vertical projection method and the character boundary are used to segment the character for actually using cases.


2011 ◽  
Vol 65 ◽  
pp. 536-541
Author(s):  
Ye Qin Wang ◽  
Liang Hai Chen ◽  
Li Yun Zhuang

In order to achieve the exact location and character recognition of license plate, firstly, this paper got binary image of license plate and done edge detection with differential operation. Secondly, it searched the license plate binary image after difference for the horizontal and vertical cut point, and determined the best cutting threshold through the experiment. Finally, it made the character segmentation by vertical projection, the recognition of license plate characters with the use of BP neural network, whose overall recognition rate is at 95.3%, and the display interface design for program transfer and results display. The experimental results showed that the location of license plate was exact and the character recognition rate was high.


2010 ◽  
Vol 20-23 ◽  
pp. 438-444 ◽  
Author(s):  
Bo Li ◽  
Zhi Yuan Zeng ◽  
Hua Li Dong ◽  
Xiao Ming Zeng

This paper proposed an algorithm for license plate recognition system(LPRS). The vertical edge was first detected by sobel color edge detector. Then, the invalid edge was removed regarding edge density. Next, the license plate(LP) image was converted into HSV color model, and by edge density template and fuzzy color information judgement, the LP region was located. Then, color-reversing judgement and tilt correction was conducted. Afterward, characters were segmented by means of vertical projection and convolution, by which character width and position can be exactly confirmed, and character recognition was conducted based on radial basis function (RBF) neural network. With a lot of samples verified in night hours and daytime under real conditions, the experimental results show that the proposed method can achieve accuracy and effectiveness in LPRS.


2017 ◽  
Vol MCSP2017 (01) ◽  
pp. 30-34
Author(s):  
Somalin Sandha ◽  
Debaraj Rana

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.


2013 ◽  
Vol 385-386 ◽  
pp. 1429-1433 ◽  
Author(s):  
Zhong Yan Liang ◽  
San Yuan Zhang

The tilt license plate correction is an important part of the license plate recognition system. Traditional correction methods are based on one theory. It is difficult to use the advantages of different approaches. We propose some methods to help improve the tile license plate correction: a bounding box selection method based on similar height and a mutual correction method based on fitted parallel straight lines. Moreover, we use wide bounding boxes to segment touched characters. If the method based on parallel lines fails, another method, such as PCA-based one, can be used for complement. Experimental results show the proposed method outperforms others.


2011 ◽  
Vol 108 ◽  
pp. 52-55 ◽  
Author(s):  
Zhan Wen Wu

The license plate location method is the key technology of license plate recognition system, new algorithm is proposed based on LOG operator detecting edge of License Plate Location. First, a large number of color plate images are preprocessed to remove the background interference information, and then rough location of license plate based on block method, search area of plate will be greatly reduced and accurate positioning the plate will be realized by LOG operator combined with projection method. Static license plate image positioning by simulation and analysis show that the method has high accuracy in license plate location.


2021 ◽  
Vol 39 (1B) ◽  
pp. 101-116
Author(s):  
Nada N. Kamal ◽  
Enas Tariq

Tilt correction is an essential step in the license plate recognition system (LPR). The main goal of this article is to provide a review of the various methods that are presented in the literature and used to correct different types of tilt that appear in the digital image of the license plates (LP). This theoretical survey will enable the researchers to have an overview of the available implemented tilt detection and correction algorithms. That’s how this review will simplify for the researchers the choice to determine which of the available rotation correction and detection algorithms to implement while designing their LPR system. This review also simplifies the decision for the researchers to choose whether to combine two or more of the existing algorithms or simply create a new efficient one. This review doesn’t recite the described models in the literature in a hard-narrative tale, but instead, it clarifies how the tilt correction stage is divided based on its initial steps. The steps include: locating the plate corners, finding the tilting angle of the plate, then, correcting its horizontal, vertical, and sheared inclination. For the tilt correction stage, this review clarifies how state-of-the-art literature handled each step individually. As a result, it has been noticed that line fitting, Hough transform, and Randon transform are the most used methods to correct the tilt of a LP.


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