Automated License Plate Recognition for Non-Helmeted Motor Riders Using YOLO and OCR

Authors

  • Chunduru Anilkumar Department of Information Technology, GMR Institute of Technology, Rajam, Andhra Pradesh, India
  • Meesala Shobha Rani School of Computer Science and Engineering, REVA University, Bangalore, Karnataka India
  • Venkatesh B Associate Professor, Department of Computer Science and Engineering, BVRIT HYDERABAD College of Engineering for Women, Hyderabad, India
  • G. Srinivasa Rao Department of Information Technology, RVR & JC College of Engineering, Guntur Andhra Pradesh, India

DOI:

https://doi.org/10.13052/jmm1550-4646.2021

Keywords:

Object detection, helmet detection, license plate number, YOLO, optical character recognition

Abstract

One of the leading causes of serious injuries in motorcycle accidents is the failure to wear a helmet, pressing the need for effective measures to encourage riders to use helmets. To stop these frequent violations of business regulations, regular observation is necessary. The proposed system is for detecting traffic violations in India related to riding motorcycles without helmets. The system utilizes deep learning-based object detection using YOLO and OCR techniques to automatically detect non-helmet riders and extract license plate numbers. The proposed system aims to improve efficiency and accuracy in detecting violations by automating the process and reducing the need for manpower. The system involves three levels of object detection: person and motorcycle/moped, helmet, and license plate. OCR is used to extract the license plate number, and all techniques are subject to predefined conditions and constraints. The system is designed to operate on video input to ensure high-speed execution, and it intends to offer a complete solution for both detection of helmet and extracting the license plate number.

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Author Biographies

Chunduru Anilkumar, Department of Information Technology, GMR Institute of Technology, Rajam, Andhra Pradesh, India

Chunduru Anilkumar received his B.Tech (Computer Science and Engineering) from Jawaharlal Nehru Technological University Kakinada, Andhra Pradesh in 2012. He received his Master of Technology in Computer Science and Engineering from Jawaharlal Nehru Technological University Hyderabad, Telangana in 2014. From 2016 onwards he is pursuing a part time Doctor of Philosophy (Ph.D) in School of Computer Science and Engineering from Vellore Institute of Technology, Vellore. He is currently working as an Assistant Professor in the Department of Information Technology at GMR Institute of Technology, Rajam, Srikakulam, Andhra Pradesh. He has published more than 30 technical papers in various international journals, conferences, and book chapters in Computer Science. He is associated with many professional bodies like ISTE, IACSIT, IAENG, CSTA (ACM), SDIWC, UACEE, CRSI and IEEE. He is in the editorial board reviewer of several international journals like International Journal of Grid and High-Performance Computing (IJGHPC), International Journal of Digital Crime and Forensics (IJDCF), Journal of Information Technology Research (JITR), International Journal of Cyber-Physical Systems (IJCPS) these journals are indexed in Scopus, SCI. His research includes Cloud computing, Network security, Fog Computing, Information Security, Cybernetics, Machine Learning.

Meesala Shobha Rani, School of Computer Science and Engineering, REVA University, Bangalore, Karnataka India

Meesala Shobha Rani received her Ph.D. from Vellore Institute of Technology in 2021, Vellore, India. She completed her M.Tech from the Karunya University, Coimbatore, India and B.Tech from JNTU, Anantapur. She is working as Assistant Professor in the School of Computer Science and Engineering at REVA University, Bangalore. She has published more than 20 technical papers in various international journals, conferences, patents, and book chapters in Computer Science. Her research includes Sentiment Analysis and Opinion Mining, Opinion Spam Detection, Text Mining, Intrusion Detection, Data Mining, Artificial Intelligence, Machine Learning, Deep Learning, and Evolutionary Optimization Techniques.

Venkatesh B, Associate Professor, Department of Computer Science and Engineering, BVRIT HYDERABAD College of Engineering for Women, Hyderabad, India

Venkatesh B obtained his B. Tech from JNTU, Anantapur in 2009. He received his Master of Technology from JNTU, Anantapur in 2013. He received his Ph.D. in 2021 from Vellore Institute of Technology, Tamil Nadu. Currently, he is working as an Associate Professor in the Department of CSE at BVRIT HYDERABAD College of Engineering for Women, Hyderabad, India. His areas of interest are data mining, Deep learning, Machine Learning, and Network Security. He has published more than 10 papers in National and International Journals.

G. Srinivasa Rao, Department of Information Technology, RVR & JC College of Engineering, Guntur Andhra Pradesh, India

G. Srinivasa Rao graduated in B. E(CSE) from Marathwada university, India in the year 1989, received master’s degree M. S in software systems from Birla Institute of Technology and Science, Pilani in 1996 and M. Tech (CSE) from JNTU Hyderabad in the year 2008, and he is pursuing Ph.D. from JNTUH, Hyderabad. He has 32 years of teaching Experience. Presently he is working as Associate Professor in the department of Information Technology, RVR & JC College of Engineering, Guntur. His research interest includes Image and Signal Processing, algorithms, and web technologies.

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Published

2024-03-29

How to Cite

Anilkumar, C., Rani, M. S., B, V., & Rao, G. S. (2024). Automated License Plate Recognition for Non-Helmeted Motor Riders Using YOLO and OCR. Journal of Mobile Multimedia, 20(02), 239–266. https://doi.org/10.13052/jmm1550-4646.2021

Issue

2024: Vol 20 Iss 2

Section

Articles