scholarly journals A Deep Learning Model of Dual-Stage License Plate Recognition Applicable to the Data Processing Industry

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Chun-Liang Tung ◽  
Ching-Hsin Wang ◽  
Bo-Syuan Peng
Keyword(s):  
Data Processing ◽  
Character Recognition ◽  
Recognition Accuracy ◽  
License Plate ◽  
License Plate Recognition ◽  
Processing Industry ◽  
Recognition Model ◽  
Traffic Violations ◽  
Detection Stage ◽  
Plate Location

Automatic License Plate Recognition (ALPR) is a widely used technology. However, due to the influence of complex environmental factors, recognition accuracy and speed of license plate recognition have been challenged and expected. Aiming to construct a sufficiently robust license plate recognition model, this study adopted multitask learning in the license plate detection stage, used the convolutional neural networks of single-stage detection, RetinaFace, and MobileNet, as approaches to license plate location, and completed the license plate sampling through the calculation of license plate skew correction. In the license plate character recognition stage, the Convolutional Recurrent Neural Network (CRNN) integrated with the loss function of the CTC model was employed as a segmentation-free and highly robust method of license plate character recognition. In this study, after the license plate recognition model, DLPR, trained the PVLP dataset of vehicle images provided by company A in Taiwan’s data processing industry, it performed tests on the PVLP dataset, indicating that its precision was 98.60%, recognition accuracy was 97.56%, and recognition speed was FPS > 21. In addition, according to the tests on the public AOLP dataset of Taiwan’s vehicles, its recognition accuracy was 97.70% and recognition speed was FPS > 62. Therefore, not only can the DLPR model be applied to the license plate recognition of real-time image streams in the future, but also it can assist the data processing industry in enhancing the accuracy of license plate recognition in photos of traffic violations and the performance of traffic service operations.

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.

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.

An Efficient Algorithm for License Plate Recognition

2013 ◽  
Vol 278-280 ◽  
pp. 1297-1300
Author(s):  
Zhong Yan Liu ◽  
Jian Yang ◽  
Hong Mei Nie
Keyword(s):  
Character Recognition ◽  
Intelligent Transportation System ◽  
Character Segmentation ◽  
Experimental Result ◽  
License Plate ◽  
License Plate Recognition ◽  
License Plate Location ◽  
Whole Process ◽  
Result Show ◽  
Plate Location

The license plate recognition(LPR) is the key technology in intelligent transportation system. This paper discusses the whole process of license plate recognition technology, include the license plate image preprocessing, license plate location, character segmentation and character recognition, and simulated it by MATLAB. The experimental result show this method can obtain good recognition effect.

Research on Identification Technology of Vehicle License Plate Based on Image Processing

2014 ◽  
Vol 513-517 ◽  
pp. 2827-2830
Author(s):  
Gui Ming Shi ◽  
Tong Wu ◽  
Hang Su ◽  
Qing Tao Wei
Keyword(s):  
Image Processing ◽  
Character Recognition ◽  
Template Matching ◽  
Intelligent Transportation System ◽  
Transport Systems ◽  
License Plate ◽  
License Plate Recognition ◽  
Tilt Correction ◽  
License Plate Location ◽  
Plate Location

Automatic vehicle license plate is an important part of intelligent transportation system. The success of the plate recognition will have a deep impact on the construction of intelligent transport systems. Image processing, tilt correction, character delimitation, character recognition and matching are main applications of vehicle license plate recognition, and the above process are implemented in matlab environment. Vehicle license plate location is implemented by vehicle license plate locating method based on edge detection and morphology filter in this article. The tilt correction mode based on Hough transform is used for license plate tilt correction section; character delimitation algorithm is used for character delimitation to achieve the vehicle license plate character segmentation; character recognition method based on template matching is chosen for character recognition section in this article, and successfully identify the license plate number.

scholarly journals Improved Automatic License Plate Recognition in Jordan Based on Ceiling Analysis

2021 ◽  
Vol 11 (22) ◽  
pp. 10614
Author(s):  
Musa Al-Yaman ◽  
Haneen Alhaj Mustafa ◽  
Sara Hassanain ◽  
Alaa Abd AlRaheem ◽  
Adham Alsharkawi ◽  
...  
Keyword(s):  
Character Recognition ◽  
Detection Accuracy ◽  
License Plate ◽  
License Plate Recognition ◽  
Size Estimation ◽  
Main Challenge ◽  
Detection Stage ◽  
Overall Performance ◽  
Candidate Regions ◽  
Automatic License Plate Recognition

The main challenge of automatic license plate recognition (ALPR) systems is that the overall performance is highly dependent upon the results of each component in the system’s pipeline. This paper proposes an improved ALPR system for the Jordanian license plates. Ceiling analysis is carried out to identify potential enhancements in each processing stage of a previously reported ALPR system. Based on the obtained ceiling analysis results, several enhancements are then suggested to improve the overall performance of the system under study. These improvements are (i) vertical-edge histogram analysis and size estimation of the candidate regions in the detection stage and (ii) de-rotation of the misaligned license plate images in the segmentation unit. These enhancements have resulted in significant improvements in the overall system performance despite a <1% increase in the execution time. The performance of the developed ALPR is assessed experimentally using a dataset of 500 images for parked and moving vehicles. The obtained results are found to be superior to those reported in equivalent systems, with a plate detection accuracy of 94.4%, character segmentation accuracy of 91.9%, and character recognition accuracy of 91.5%.

scholarly journals Design and implementation of lightweight vehicle license plate recognition module utilizing open CV and Tesseract OCR library

2018 ◽  
Vol 7 (3.3) ◽  
pp. 350
Author(s):  
Yong Gyu Jung ◽  
Hee Wan Kim
Keyword(s):  
Open Source ◽  
Character Recognition ◽  
Candidate Region ◽  
License Plate ◽  
License Plate Recognition ◽  
Software Module ◽  
Static Image ◽  
Traffic Violations ◽  
Plate Area ◽  
Vehicle License Plate Recognition

Background/Objectives: In order to recognize the license plates automatically, we design and implement a vehicle license plate recognition module that extracts characters of license plate area using open source OpenCV and Terreract OCR library.Methods/Statistical analysis: The static image was binarized using OpenCV 's banalization function. After binarizing the image by adjusting the pixel values between adjacent pixels, the candidate region judged a license plate was derived. The final candidate was derived according to the proposed algorithm in the candidate region. The extracted plate area was analyzed by using the Tesseract OCR library, and characters were extracted as a character string.Findings: The vehicle license plate recognition module relates to character recognition in the field of computer vision. In this paper, we designed and implemented a module that recognizes a license plate by using open source, applying a proposed algorithm to a moving object as a static image. The proposed module is a relatively lightweight software module and can be used in other applications. It is possible to install the camera at the entrance of the apartment and can read the license plate to identify whether it is a resident or not. When speeding and traffic violations occur on the highway, the vehicle numbers can be automatically stored and managed in the database. In addition, there is an advantage that it can be applied to various character recognition applications through modification of a slight algorithm in the module.Improvements/Applications: In addition to character recognition, the OpenCV library can be applied to various fields such as pattern recognition, object tracking, and motion recognition. Therefore, we will be able to create technologies corresponding to various services that are becoming automated and unmanned.  

scholarly journals Automatic Iranian Vehicle License Plate Recognition System Based on Support Vector Machine (SVM) Algorithms

2013 ◽  
Vol 2 (1) ◽  
pp. 161-174
Author(s):  
Mahdi Aghaie ◽  
Fatemeh Shokri ◽  
Meisam Yadolah Zade Tabari
Keyword(s):  
Character Recognition ◽  
Intelligent System ◽  
Recognition System ◽  
Support Vector ◽  
License Plate ◽  
License Plate Recognition ◽  
The Road ◽  
Vehicle License Plate Recognition ◽  
Plate Location ◽  
On The Road

There are far more cars on the road now than there used to be. Therefore, Controlling and managing the huge volume of traffic is virtually impossible without the use of computer technology. This paper represents design and implement of an intelligent system for license plate recognition based on three main steps. This process includes the detection of license plate location, character segmentation and character recognition. In this study, we used Classifier svm to detect the characters. According to the results, the performance of the proposed system is better compared to similar algorithms such as neural network. It is worth mentioning that Recognition Approach is tested in various conditions and results are described.   Keyword- Vehicle license plate recognition, Morphology Operations, Histogram, The edge detection, Classifier SVMDOI: 10.18495/comengapp.21.161174

License Plate Location Method Based on LOG Edge Detection Operator

2011 ◽  
Vol 108 ◽  
pp. 52-55 ◽  
Author(s):  
Zhan Wen Wu
Keyword(s):  
Recognition System ◽  
License Plate ◽  
License Plate Recognition ◽  
Block Method ◽  
Key Technology ◽  
Location Method ◽  
License Plate Location ◽  
Color Plate ◽  
Search Area ◽  
Plate Location

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.

scholarly journals Residential Area Surveillance and Parking System

2020 ◽  
Vol 9 (5) ◽  
pp. 602-606
Keyword(s):  
Character Recognition ◽  
Optical Character Recognition ◽  
Residential Area ◽  
High Rate ◽  
Identification System ◽  
License Plate ◽  
License Plate Recognition ◽  
Position Effects ◽  
Plain Text ◽  
Alert Message

The vehicles playing the vital role in our day to day life for transport, and some of the vehicles violates the traffic rules are also increasing, vehicle theft, unnecessary entering into highly restricted areas, increased number of accidents lead to increase in the rate of crime slowly. The vehicle had its own identity it should be recognized which plays the major role in the world. For recognition of the vehicles which are used commonly in the field of safety and security system, LPDR plays a major role and the vehicle registration number is recognized at some certain distance accurately. License Plate recognition is the most efficient and cost effective technique used for detection and recognition purposes. Automatic license plate recognition (ALPR) is used for finding the location of the license plate in the vehicle. These methods and techniques vary based on the conditions like, quality of the image, vehicle on a fine-tuned position, effects of lighting, type of image, etc. The objective is to design an efficient automatic conveyance identification system of sanctioned or unauthorized in the residential societies by utilizing the conveyance number plate. By getting the car image from the surveillance camera in the entrance, we recognizing the number plate and the characters are extracted using OCR (optical character recognition). It converts the character in the image to plain text. Then the plain text of the license plate is cross-verified with the database to check whether the vehicle belongs to residents or visitor. It sends the alert message to the security official when a new visitor request method in a residential area. The log details are stored separately for the resident and visitor in the database. It also provides the details about the parking area availability in the residential area. By calculating the number of vehicles in and out of the area, the detail or availability parking slot is displayed and it sis robust to the size, lighting effects with high rate of detection.

License Plate Recognition for Stolen Vehicles Using Optical Character Recognition

2022 ◽  
pp. 575-583
Author(s):  
Armand Christopher Luna ◽  
Christian Trajano ◽  
John Paul So ◽  
Nicole John Pascua ◽  
Abraham Magpantay ◽  
...  
Keyword(s):  
Character Recognition ◽  
Optical Character Recognition ◽  
License Plate ◽  
License Plate Recognition ◽  
Optical Character
Sign in / Sign up

Export Citation Format

Share Document