A novel character segmentation-reconstruction approach for license plate recognition

2019 ◽  
Vol 131 ◽  
pp. 219-239 ◽  
Author(s):  
Vijeta Khare ◽  
Palaiahnakote Shivakumara ◽  
Chee Seng Chan ◽  
Tong Lu ◽  
Liang Kim Meng ◽  
...  
2013 ◽  
Vol 760-762 ◽  
pp. 1638-1641 ◽  
Author(s):  
Chun Yu Chen ◽  
Bao Zhi Cheng ◽  
Xin Chen ◽  
Fu Cheng Wang ◽  
Chen Zhang

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.


2014 ◽  
Vol 556-562 ◽  
pp. 2623-2627
Author(s):  
Feng Ran ◽  
Fa Yu Zhang ◽  
Mei Hua Xu

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.


2011 ◽  
Vol 267 ◽  
pp. 778-782 ◽  
Author(s):  
Juan Hua Zhu ◽  
Ang Wu ◽  
Juan Fang Zhu

A rapid and convenient method of license plate recognition is discussed. The color plates are preprocessed by transform gray-scale transformation and image enhancement. The license plate is located by edge detection and region search algorithm, and the character segmentation is made by projection. Finally, the template is matched, and the license plate number is recognized quickly and accurately. The experiment shows that the method used in this paper can achieve better recognition results.


2013 ◽  
Vol 278-280 ◽  
pp. 1297-1300
Author(s):  
Zhong Yan Liu ◽  
Jian Yang ◽  
Hong Mei Nie

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.


Sensors ◽  
2019 ◽  
Vol 19 (13) ◽  
pp. 3015 ◽  
Author(s):  
Farman Ullah ◽  
Hafeez Anwar ◽  
Iram Shahzadi ◽  
Ata Ur Rehman ◽  
Shizra Mehmood ◽  
...  

The paper proposes a sensors platform to control a barrier that is installed for vehicles entrance. This platform is automatized by image-based license plate recognition of the vehicle. However, in situations where standardized license plates are not used, such image-based recognition becomes non-trivial and challenging due to the variations in license plate background, fonts and deformations. The proposed method first detects the approaching vehicle via ultrasonic sensors and, at the same time, captures its image via a camera installed along with the barrier. From this image, the license plate is automatically extracted and further processed to segment the license plate characters. Finally, these characters are recognized with the help of a standard optical character recognition (OCR) pipeline. The evaluation of the proposed system shows an accuracy of 98% for license plates extraction, 96% for character segmentation and 93% for character recognition.


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.


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