License Plate Detection and Recognition System for All Types of Bangladeshi Vehicles Using Multi-step Deep Learning Model

Author(s):  
Homaira Huda Shomee ◽  
Ataher Sams
2020 ◽  
Vol 8 (6) ◽  
pp. 5730-5737

Digital Image Processing is application of computer algorithms to process, manipulate and interpret images. As a field it is playing an increasingly important role in many aspects of people’s daily life. Even though Image Processing has accomplished a great deal on its own, nowadays researches are being conducted in using it with Deep Learning (which is part of a broader family, Machine Learning) to achieve better performance in detecting and classifying objects in an image. Car’s License Plate Recognition is one of the hottest research topics in the domain of Image Processing (Computer Vision). It is having wide range of applications since license number is the primary and mandatory identifier of motor vehicles. When it comes to license plates in Ethiopia, they have unique features like Amharic characters, differing dimensions and plate formats. Although there is a research conducted on ELPR, it was attempted using the conventional image processing techniques but never with deep learning. In this proposed research an attempt is going to be made in tackling the problem of ELPR with deep learning and image processing. Tensorflow is going to be used in building the deep learning model and all the image processing is going to be done with OpenCV-Python. So, at the end of this research a deep learning model that recognizes Ethiopian license plates with better accuracy is going to be built.


IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 201317-201330
Author(s):  
Ali Tourani ◽  
Asadollah Shahbahrami ◽  
Sajjad Soroori ◽  
Saeed Khazaee ◽  
Ching Yee Suen

2016 ◽  
Vol 137 (9) ◽  
pp. 31-34 ◽  
Author(s):  
Poonam Bhogale ◽  
Archit Save ◽  
Vitrag Jain ◽  
Saurabh Parekh

2021 ◽  
Vol 81 ◽  
pp. 103726
Author(s):  
Deepika Chauhan ◽  
Ashok Kumar ◽  
Pradeep Bedi ◽  
Vijay Anant Athavale ◽  
D. Veeraiah ◽  
...  

2021 ◽  
Vol 11 (14) ◽  
pp. 6292
Author(s):  
Tae-Gu Kim ◽  
Byoung-Ju Yun ◽  
Tae-Hun Kim ◽  
Jae-Young Lee ◽  
Kil-Houm Park ◽  
...  

In this study, we have proposed an algorithm that solves the problems which occur during the recognition of a vehicle license plate through closed-circuit television (CCTV) by using a deep learning model trained with a general database. The deep learning model which is commonly used suffers with a disadvantage of low recognition rate in the tilted and low-resolution images, as it is trained with images acquired from the front of the license plate. Furthermore, the vehicle images acquired by using CCTV have issues such as limitation of resolution and perspective distortion. Such factors make it difficult to apply the commonly used deep learning model. To improve the recognition rate, an algorithm which is a combination of the super-resolution generative adversarial network (SRGAN) model, and the perspective distortion correction algorithm is proposed in this paper. The accuracy of the proposed algorithm was verified with a character recognition algorithm YOLO v2, and the recognition rate of the vehicle license plate image was improved 8.8% from the original images.


Array ◽  
2020 ◽  
Vol 8 ◽  
pp. 100040
Author(s):  
Ibtissam Slimani ◽  
Abdelmoghit Zaarane ◽  
Wahban Al Okaishi ◽  
Issam Atouf ◽  
Abdellatif Hamdoun

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