Barrier Access Control Using Sensors Platform and Vehicle License Plate Characters Recognition.

barrier control features extraction license plate recognition machine learning algorithms raspberry-pi sensors platform vehicle detection

Journal

Sensors (Basel, Switzerland)
ISSN: 1424-8220
Titre abrégé: Sensors (Basel)
Pays: Switzerland
ID NLM: 101204366

Informations de publication

Date de publication:
09 Jul 2019
Historique:
received: 16 04 2019
revised: 15 06 2019
accepted: 18 06 2019
entrez: 21 7 2019
pubmed: 22 7 2019
medline: 22 7 2019
Statut: epublish

Résumé

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.

Identifiants

pubmed: 31323933
pii: s19133015
doi: 10.3390/s19133015
pmc: PMC6650970
pii:
doi:

Types de publication

Journal Article

Langues

eng

Subventions

Organisme : Ignite R&D Pakistan
ID : Ignite R&D Pakistan

Références

IEEE Trans Pattern Anal Mach Intell. 1986 Jun;8(6):679-98
pubmed: 21869365
Sensors (Basel). 2012;12(6):8355-70
pubmed: 22969404
ScientificWorldJournal. 2014;2014:679849
pubmed: 25152921

Auteurs

Farman Ullah (F)

Department of Electrical & Computer Engineering, COMSATS University Islamabad-Attock Campus, Attock 43600, Pakistan.

Hafeez Anwar (H)

Department of Electrical & Computer Engineering, COMSATS University Islamabad-Attock Campus, Attock 43600, Pakistan.

Iram Shahzadi (I)

Department of Electrical & Computer Engineering, COMSATS University Islamabad-Attock Campus, Attock 43600, Pakistan.

Ata Ur Rehman (A)

Department of Electrical & Computer Engineering, COMSATS University Islamabad-Attock Campus, Attock 43600, Pakistan.

Shizra Mehmood (S)

Department of Electrical & Computer Engineering, COMSATS University Islamabad-Attock Campus, Attock 43600, Pakistan.

Sania Niaz (S)

Department of Electrical & Computer Engineering, COMSATS University Islamabad-Attock Campus, Attock 43600, Pakistan.

Khalid Mahmood Awan (K)

Department of Computer Sciences, COMSATS University Islamabad-Attock Campus, Attock 43600, Pakistan.

Ajmal Khan (A)

Department of Electrical & Computer Engineering, COMSATS University Islamabad-Attock Campus, Attock 43600, Pakistan.

Daehan Kwak (D)

Department of Computer Science, Kean University, Union, NJ 07083, USA. dkwak@kean.edu.

Classifications MeSH