License plate detection and recognition based on YOLOv3 and ILPRNET

2021 ◽  
Author(s):  
Yongjie Zou ◽  
Yongjun Zhang ◽  
Jun Yan ◽  
Xiaoxu Jiang ◽  
Tengjie Huang ◽  
...  
Keyword(s):  
License Plate ◽  
License Plate Detection ◽  
Detection And Recognition

scholarly journals A Robust Deep Learning Approach for Automatic Iranian Vehicle License Plate Detection and Recognition for Surveillance Systems

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 201317-201330
Author(s):  
Ali Tourani ◽  
Asadollah Shahbahrami ◽  
Sajjad Soroori ◽  
Saeed Khazaee ◽  
Ching Yee Suen
Keyword(s):  
Deep Learning ◽  
License Plate ◽  
Learning Approach ◽  
Surveillance Systems ◽  
License Plate Detection ◽  
Detection And Recognition

scholarly journals Digital License Plate Detection and Recognition with Improved Vertical Edge Detection and Template Matching

IJARCCE ◽  
2017 ◽  
pp. 224-228
Author(s):  
A F M Shahab Uddin ◽  
Feroza Naznin ◽  
Md. Alamgir Hossain ◽  
Md. Zahidul Islam
Keyword(s):  
Edge Detection ◽  
Template Matching ◽  
License Plate ◽  
Vertical Edge ◽  
License Plate Detection ◽  
Detection And Recognition

scholarly journals Parking entrance control using license plate detection and recognition

2019 ◽  
Vol 15 (1) ◽  
pp. 476 ◽  
Author(s):  
Mohamed Sayed Farag ◽  
Mostafa Mohamed Mohie El Din ◽  
Hassan Ahmed Elshenbary
Keyword(s):  
Recognition Rate ◽  
Correlation Method ◽  
Good Method ◽  
Color Filter ◽  
License Plate ◽  
Image Size ◽  
Smart Systems ◽  
Smart Parking ◽  
License Plate Detection ◽  
Detection And Recognition

<p>There is no doubt that car parking is a very challenging and interesting topic of surveillance. In the recent years, a lot of smart systems for parking lot access control were developed to control and register the car data. The aim of this paper is to use image processing methods to control the entrance of a smart parking. The steps of car plate recognition are: preprocessing, License plate detection, character extraction and recognition. In the step of preprocessing, image was enhanced and noise was reduced. After preprocessing stage, color filter was used to detect the plate region. In case of large image size DWT was used for feature extraction and decreased the time of the detection stage. In the stage of character segmentation, the image is converted from grayscale to binary according to a given threshold. Filtering the binary image after using the morphological operation method, the largest objects are determined as the segmented plate characters. Finally, the correlation method was used to recognize the segmented characters. In case of similarity, SVM was used as a good classifier. Experimental results using matlab software, view that the proposed method increase the plate detection and recognition rates. It achieved aver- age 97.8% detection rate, 98% segmentation rate and 97% recognition rate, So it will be a good method for smart parking entrance control.</p>

Sign in / Sign up

Export Citation Format

Share Document