Using Synthetic Images for Deep Learning Recognition Process on Automatic License Plate Recognition

Author(s):  
Saulo Cardoso Barreto ◽  
Jorge Albuquerque Lambert ◽  
Flávio de Barros Vidal
2021 ◽  
pp. 211-226
Author(s):  
Riccardo Balia ◽  
Silvio Barra ◽  
Salvatore Carta ◽  
Gianni Fenu ◽  
Alessandro Sebastian Podda ◽  
...  

Author(s):  
Bhavin Dhedhi ◽  
Prathamesh Datar ◽  
Anuj Chiplunkar ◽  
Kashish Jain ◽  
Amrith Rangarajan ◽  
...  

2019 ◽  
Vol 24 (1) ◽  
pp. 23-43 ◽  
Author(s):  
Diogo M. F. Izidio ◽  
Antonyus P. A. Ferreira ◽  
Heitor R. Medeiros ◽  
Edna N. da S. Barros

Object Detection is one of the most important concepts of Computer Vision which is used in various areas like Medical Field, Security, Self Driving cars, Automated vehicle systems etc.We choose the application of Automatic License plate Recognition. Automatic License Plate Recognition is an emerging technology which is helpful in many fields and at the same time is challenging. It’s challenging because we need to get the accurate recognition of the characters in a number plate. In practical applications where sometimes the images are captured in the worst weather condition, bad lighting, wind. And to the addition, license plates are often dirty or blackened due to the smoke, half broken , or having scratches on certain characters and detection of too many license plates in a single frame. All these will act as the obstacles in developing an effective ALPR system. So basically, this is a system where recognition of characters from images using Computer Vision techniques are performed. This system is implemented in many fields like parking lots, private and public entrances, toll gates, theft control, checking the authentication of a vehicle. Procedure followed in this paper are, first capturing images from camera then loading that into system, preprocessing done using OpenCV library. Then we use Attention OCR a deep learning model to recognize the characters from an image. And later display that in the GUI and store them in the databases for different operations later.


Author(s):  
Pedro Ferreira Alves Pinto ◽  
Antonio José G. Busson ◽  
João P. Forny de Melo ◽  
Sérgio Colcher ◽  
Ruy Luiz Milidiú

Vehicle’s license plate detection and recognition is a task with several practical applications. It can be applied, for example, in the security segment, identifying stolen cars and controlling cars entry/exit in private areas. This work presents a Deep Learning based tool that uses the cascaded YOLOv3 to simultaneously detect and recognize vehicle plate. In experiments performed, our tool got a recall of 95% in plate detection and 96.2% accuracy in the recognition of the 7 characters of the license plate.


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.


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