Research on License Plate Recognition System Based on Computer Vision

2011 ◽  
Vol 65 ◽  
pp. 536-541
Author(s):  
Ye Qin Wang ◽  
Liang Hai Chen ◽  
Li Yun Zhuang
Keyword(s):  
Interface Design ◽  
Character Recognition ◽  
Recognition Rate ◽  
Recognition System ◽  
Binary Image ◽  
License Plate ◽  
License Plate Recognition ◽  
Vertical Projection ◽  
Differential Operation ◽  
Program Transfer

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.

scholarly journals An Adaptive Approach for Multi-National Vehicle License Plate Recognition Using Multi-Level Deep Features and Foreground Polarity Detection Model

2020 ◽  
Vol 10 (6) ◽  
pp. 2165 ◽  
Author(s):  
Muhammad Ali Raza ◽  
Chun Qi ◽  
Muhammad Rizwan Asif ◽  
Muhammad Armoghan Khan
Keyword(s):  
Character Recognition ◽  
Recognition Rate ◽  
Generalized Solution ◽  
Recognition System ◽  
Vital Role ◽  
Transport Systems ◽  
Support Vector ◽  
License Plate ◽  
License Plate Recognition ◽  
Detection Model

License plate recognition system (LPR) plays a vital role in intelligent transport systems to build up smart environments. Numerous country specific methods have been proposed successfully for an LPR system, but there is a need to find a generalized solution that is independent of license plate layout. The proposed architecture is comprised of two important LPR stages: (i) License plate character segmentation (LPCS) and (ii) License plate character recognition (LPCR). A foreground polarity detection model is proposed by using a Red-Green-Blue (RGB) channel-based color map in order to segment and recognize the LP characters effectively at both LPCS and LPCR stages respectively. Further, a multi-channel CNN framework with layer aggregation module is proposed to extract deep features, and support vector machine is used to produce target labels. Multi-channel processing with merged features from different-level convolutional layers makes output feature map more expressive. Experimental results show that the proposed method is capable of achieving high recognition rate for multinational vehicles license plates under various illumination conditions.

Automatic License Plate Recognition System

2010 ◽  
Vol 20-23 ◽  
pp. 438-444 ◽  
Author(s):  
Bo Li ◽  
Zhi Yuan Zeng ◽  
Hua Li Dong ◽  
Xiao Ming Zeng
Keyword(s):  
Character Recognition ◽  
Rbf Neural Network ◽  
Recognition System ◽  
Edge Density ◽  
Color Model ◽  
License Plate ◽  
License Plate Recognition ◽  
Color Information ◽  
Vertical Projection ◽  
Hsv Color Model

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.

scholarly journals Development of Iraqi License Plate Recognition System based on Canny Edge Detection Method

2020 ◽  
Vol 26 (7) ◽  
pp. 115-126
Author(s):  
Bydaa Ali Hussain ◽  
Mohammed Sadoon Hathal
Keyword(s):  
Edge Detection ◽  
Character Recognition ◽  
Recognition Rate ◽  
Recognition System ◽  
Detection Algorithm ◽  
License Plate ◽  
License Plate Recognition ◽  
Canny Edge Detection ◽  
Canny Edge ◽  
On The Road

In recent years, there has been expanding development in the vehicular part and the number of vehicles moving on the road in all the sections of the country. Vehicle number plate identification based on image processing is a dynamic area of this work; this technique is used for security purposes such as tracking of stolen cars and access control to restricted areas. The License Plate Recognition System (LPRS) exploits a digital camera to capture vehicle plate numbers is used as input to the proposed recognition system. Basically, the developing system is consist of three phases, vehicle license plate localization, character segmentation, and character recognition, the License Plate (LP) detection is presented using canny Edge detection algorithm, Connect Component Analysis (CCA) have been exploited for segmenting characters. Finally, a Multi-Layer Perceptron Artificial Neural Network (MLPANN) model is utilized to recognize and detect the vehicle license plate characters, and hence the results are displayed as a text on GUI. The proposed system successfully identified and recognized multi_style Iraqi license plates using different image situations and it was evaluated based on different metrics performance, achieving an overall system performance of 91.99%. This results shows the effectiveness of the proposed method compared with other existing methods, whose average recognition rate is 86% and the average processing time of one image is 0.242s which proves the practicality of the proposed method.

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.

Research of License Plate Recognition System Based on Labview

2015 ◽  
Vol 734 ◽  
pp. 646-649
Author(s):  
Zhong Hua Hu ◽  
Chen Tang
Keyword(s):  
Virtual Instrument ◽  
Character Recognition ◽  
Traffic Management ◽  
Intelligent Transportation System ◽  
Recognition System ◽  
License Plate ◽  
Morphological Operations ◽  
License Plate Recognition ◽  
Plate Location ◽  
Traffic Management System

The vehicle license plate recognition system is the intelligent traffic management system based on the image and the character recognition technology, which is an important part of the intelligent transportation system. This paper introduces a method of vehicle license plate location based on edge detection and morphological operations, virtual instrument is combined with machine vision of the license plate recognition method [1]. Finally the license plate number of the vehicle is get. Experiment results show that such method can simplify the algorithm and has some correct location rate.

Research and Design of License Plate Recognition System

2014 ◽  
Vol 556-562 ◽  
pp. 2623-2627
Author(s):  
Feng Ran ◽  
Fa Yu Zhang ◽  
Mei Hua Xu
Keyword(s):  
Adaptive Learning ◽  
Character Recognition ◽  
Complete System ◽  
Recognition System ◽  
Morphological Processing ◽  
Character Segmentation ◽  
License Plate ◽  
License Plate Recognition ◽  
Research And Design ◽  
Speed And Accuracy

Introduce a complete system of license plate recognition: using morphological processing and priori knowledge of license plate to discern the location of license plate, accomplishing tilt correction through Radon transform, then fulfilling character segmentation of accurate positioning license plate by projection, finishing character recognition through BP neural network which was improved by the use of adaptive learning rate and momentum factor. With the programming and verification on Matlab experimental platform, experimental results show that we can have a preferable recognition speed and accuracy.

Research on Pre-Processing Methods for License Plate Recognition

2021 ◽  
Vol 11 (1) ◽  
pp. 47-79
Author(s):  
Weifang Zhai ◽  
Terry Gao ◽  
Juan Feng
Keyword(s):  
Edge Detection ◽  
Mathematical Morphology ◽  
Traffic Management ◽  
Recognition System ◽  
Character Segmentation ◽  
License Plate ◽  
License Plate Recognition ◽  
Vertical Projection ◽  
License Plate Location ◽  
Plate Location

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.

Research of License Plate Recognition under Complex Environment

2014 ◽  
Vol 989-994 ◽  
pp. 2569-2575
Author(s):  
Feng Gao ◽  
Zhong Jian Dai ◽  
Kun Zhou ◽  
Ya Ping Dai
Keyword(s):  
Recognition Accuracy ◽  
Recognition Rate ◽  
Recognition System ◽  
License Plate ◽  
License Plate Recognition ◽  
Complex Environment ◽  
Color Information ◽  
Location Algorithm ◽  
Character Feature ◽  
Set Up

In order to improve the license plate recognition accuracy under complex environment, a new license location algorithm combining vertical edge detection, color information of the license plate and mathematical morphology is presented in this paper. For balance of computing load and recognition accuracy, a “200-d” character feature rule is designed, and the “200-d” feature is used as the input of BP neural network to recognize the characters. Based on the above-mentioned methods, a license plate recognition system is set up, which can locate and recognize the license plate effectively, even when the resolution of pictures and the position of vehicles in the pictures are not fixed. Experimental results indicate that the recognition rate of the algorithm reaches 90.5%.

Research and Realization for Embedded License Plate Recognition System

2013 ◽  
Vol 411-414 ◽  
pp. 1015-1019
Author(s):  
Yuan Ning ◽  
Yao Wen Liu ◽  
Yan Bin Zhang ◽  
Hao Yuan
Keyword(s):  
Power Consumption ◽  
System Design ◽  
Character Recognition ◽  
Template Matching ◽  
Median Filter ◽  
Recognition System ◽  
License Plate ◽  
License Plate Recognition ◽  
Design Constraints ◽  
Recognition Phase

In this paper, the embedded license plate recognition system based on TMS320DM642 is researched. During the design, median filter, threshold, and morphology closing operations are used to obtain license plate region, then segmented into disjoint characters for the character recognition phase, where the template matching is used to identify the characters. Embedded License Plate Recognition System, being smaller, has less power consumption with respect to software based LPR systems. The resulting hardware is suitable for applications where cost, compactness, and efficiency are system design constraints.

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