License plate recognition for campus auto-gate system

Nur Liyana Yaacob, Ammar Ahmed Alkahtani, Fuad M. Noman, Ahmad Wafi Mahmood Zuhdi, Dhuha Habeeb

Research output: Contribution to journalArticleResearch

1 Citation (Scopus)

Abstract

Automatic licence plate recognition (LPR) has been a subject of study for the last few decades. Considering the recent advancements in machine learning methods and portable devices, this increasingly attracting researchers’ interest to provide more reliable LPR systems. Several LPR techniques have been reported in the literature in different intelligent transportation applications and surveillance systems, and yet a ropust LPR system remains a challenging research task. Because the performance of current techniques is subject to several factors and local conditions, this paper aims to explore the use of LPR in a specific application; i.e. Automatic plate recognition to monitor the entry and exit of vehicles at the university campus gates. Implementing an auto-gate system is an important application for a smooth control of flowing traffic especially during peak hours. We propose an automated system with the ability to capture, verify and recognize the license plates using image processing-based techniques. The system is aimed to work alongside existing access cards and other gate remote controls. Experimental evaluation of the system reveals a detection accuracy of 91.58%, a successful plate number segmentation rate of 91% and 80% accuracy of plate recognition.

Original languageEnglish
Pages (from-to)128-136
Number of pages9
JournalIndonesian Journal of Electrical Engineering and Computer Science
Volume21
Issue number1
DOIs
Publication statusPublished - Jan 2021
Externally publishedYes

Keywords

  • Campus auto-gate system
  • Image processing
  • License plate recognition

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