skip to main content
Language:
Search Limited to: Search Limited to: Resource type Show Results with: Show Results with: Search type Index

Text extraction and recognition method for license plates

E3S web of conferences, 2023-01, Vol.469, p.69 [Peer Reviewed Journal]

ISSN: 2267-1242 ;EISSN: 2267-1242 ;DOI: 10.1051/e3sconf/202346900069

Full text available

Citations Cited by
  • Title:
    Text extraction and recognition method for license plates
  • Author: Moussaoui, Hanae ; El Akkad, Nabil ; Benslimane, Mohamed
  • Sallem, A. ; Raihani, A. ; Benhala, B. ; Qbadou, M. ; Boukili, B.
  • Subjects: easyocr ; image processing ; text extraction ; text recognition
  • Is Part Of: E3S web of conferences, 2023-01, Vol.469, p.69
  • Description: Text extraction from images has always been challenging, especially if the image is taken under bad conditions, like lightning and noise that can influence text detection and recognition. This paper introduces a novel text extraction and recognition technique applied to the case study license plates. The main idea of this study is to detect the license plate in an input image and try to figure out the original country of the car based on the license plate. To accomplish this task, we first started collecting images from the internet, which were about 100 images. Afterward, we extracted the license plate using machine learning methods. Subsequently, we applied k-means clustering as well as thresholding in order to segment the extracted license plate and make the character recognition task easier. Thereafter, a sequence of techniques were applied, such as resizing and cropping the image to limit the wanted area of the desired character we want to extract. The last part of the proposed method is reading the text from the image using EasyOcr method, and using the function find in order to search for the character or the word. his proposed method achieved satisfactory results in detection where we achieved an accuracy of 87%, and a recognition of 97%. As for finding the ‘word’ part, the algorithm succeeded in all the examples.
  • Publisher: EDP Sciences
  • Language: English
  • Identifier: ISSN: 2267-1242
    EISSN: 2267-1242
    DOI: 10.1051/e3sconf/202346900069
  • Source: EDP Open
    ROAD: Directory of Open Access Scholarly Resources
    ProQuest Central
    DOAJ Directory of Open Access Journals
Back to results list
INSPIRE LIBRARY - TON DUC THANG UNIVERSITY (84-028) 37 755 057 Feedback
19 Nguyen Huu Tho St. Dist.7, HCM thuvien@tdtu.edu.vn

Copyright © 2017 INSPIRE LIBRARY - TON DUC THANG UNIVERSITY

Searching Remote Databases, Please Wait