Enhanced Automatic License Plate Detection and Recognition using CLAHE and YOLOv11 for Seat Belt Compliance Detection

Authors

  • Sutikno Department of Informatics, Faculty of Science and Mathematics, Diponegoro University, Indonesia
  • Aris Sugiharto Department of Informatics, Faculty of Science and Mathematics, Diponegoro University, Indonesia
  • Retno Kusumaningrum Department of Informatics, Faculty of Science and Mathematics, Diponegoro University, Indonesia
Volume: 15 | Issue: 1 | Pages: 20271-20278 | February 2025 | https://doi.org/10.48084/etasr.9629

Abstract

Traffic accidents caused by seat belt violations remain a severe problem in low-income countries. Identifying the vehicles of these violators is vital for enhancing safety. Therefore, this research develops a vehicle license plate detection and recognition system to support this problem. The proposed system was divided into three subsystems: windshield detection, license plate detection, and character recognition. The windshield detection subsystem used the You Only Look Once (YOLOv11) model. License plate detection combined the determination of the Region Of Interest (ROI) and YOLOv11. Meanwhile, character recognition combined the Contrast Limited Adaptive Histogram Equalization (CLAHE) algorithm and YOLOv11. YOLOv11 is the latest version of YOLO, which is faster and more efficient than the previous version, and CLAHE enhances the contrast of the image dataset, improving its quality. The dataset was collected from highways and toll roads in Semarang, Indonesia. The test results for windshield detection showed that the YOLOv11n model produced higher precision and faster detection time than YOLOv11m and YOLOv8m. The test results for license plate detection showed that the proposed method achieved perfect precision and recall. Meanwhile, the test results for character recognition indicated that the proposed method produced higher precision and average precision than YOLOv11n alone. The proposed method can produce precision and average precision for character recognition of 0.922 and 0.931, respectively. This research can potentially be used for automatic and real-time identification of car license plates for violators who do not wear seat belts on the highway.

Keywords:

windshield detection, license plate detection, character recognition, CLAHE, YOLOv11

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References

"The top 10 causes of death," World Health Organization. https://www.who.int/news-room/fact-sheets/detail/the-top-10-causes-of-death.

N. K. Al-Shammari and S. M. H. Darwish, "In-depth Sampling Study of Charactersitics of Vehcile Crashes in Saudi Arabia," Engineering, Technology & Applied Science Research, vol. 9, no. 5, pp. 4724–4728, Oct. 2019.

H. Guo, H. Lin, S. Zhang, and S. Li, "Image-based seat belt detection," in Proceedings of 2011 IEEE International Conference on Vehicular Electronics and Safety, Beijing, China, 2011, pp. 161–164.

W. Li, J. Lu, Y. Li, Y. Zhang, J. Wang, and H. Li, "Seatbelt detection based on cascade Adaboost classifier," in 2013 6th International Congress on Image and Signal Processing, Hangzhou, China, 2013, pp. 783–787.

B. Zhou, L. Chen, J. Tian, and Z. Peng, "Learning-based seat belt detection in image using salient gradient," in 2017 12th IEEE Conference on Industrial Electronics and Applications, Siem Reap, Cambodia, 2017, pp. 547–550.

R. A. Kapdi, P. Khanpara, R. Modi, and M. Gupta, "Image-based Seat Belt Fastness Detection using Deep Learning," Scalable Computing: Practice and Experience, vol. 23, no. 4, pp. 441–455, Dec. 2022.

J. Luo, J. Lu, and G. Yue, "Seatbelt detection in road surveillance images based on improved dense residual network with two-level attention mechanism," Journal of Electronic Imaging, vol. 30, no. 3, Jun. 2021, Art. no. 033036.

Z. Wang and Y. Ma, "Detection and recognition of stationary vehicles and seat belts in intelligent Internet of Things traffic management system," Neural Computing and Applications, vol. 34, no. 5, pp. 3513–3522, Mar. 2022.

S. B. Khalid and B. Hazela, "Employing Real-Time Object Detection for Traffic Monitoring," in Proceedings of the International Conference on Innovative Computing & Communication, New Delhi, India, 2021.

S. A. Ahmed and S. Dixit, "Number Plate and Logo Identification using Machine Learning Approches," Journal of Theoretical and Applied Information Technology, vol. 102, no. 3, pp. 1023–1036, Feb. 2024.

B. Kumar, K. Kumari, P. Banerjee, and P. Jha, "An Implementation of Automatic Number Plate Detection and Recognition using AI," in 2023 International Conference on Advances in Computing, Communication and Applied Informatics, Chennai, India, 2023, pp. 1–9.

R. Antar, S. Alghamdi, J. Alotaibi, and M. Alghamdi, "Automatic Number Plate Recognition of Saudi License Car Plates," Engineering, Technology & Applied Science Research, vol. 12, no. 2, pp. 8266–8272, Apr. 2022.

A. Sufiun, Md. H. I. Bijoy, N. R. Chakraborty, and M. A. A. K. Akash, "Automatic Bengali Number Plate Detection and Authentication using YOLO-V4 and YOLO-V5," in 2023 26th International Conference on Computer and Information Technology, Cox's Bazar, Bangladesh, 2023, pp. 1–6.

R. Kala, K. Dharani, R. Harini, A. Niranjanaa, and M. Sowmiya, "Automatic Number Plate Detection With Yolov5 and OCR Methods," in 2024 International Conference on Knowledge Engineering and Communication Systems, Chikkaballapur, India, 2024, pp. 1–5.

H. U. Iyer and S. Dhavale, "Automatic Number Plate and Face Recognition System for Secure Gate Entry into Military Establishments," in 2024 International Conference on Smart Systems for applications in Electrical Sciences, Tumakuru, India, 2024, pp. 1–6.

K. Vijayalakshmi, M. Dhanamalar, V. A. Lepakshi, and S. Jamtsho, "Smart Checkpoint Management System for Automatic Number Plate Recognition in Bhutan Vehicles Using OCR Technique," SN Computer Science, vol. 5, no. 5, May 2024, Art. no. 579.

O. Sarkar, S. Sinha, A. K. Jena, A. K. Parida, N. Parida, and R. K. Parida, "Automatic Number Plate Character Recognition using Paddle-OCR," in 2024 International Conference on Innovations and Challenges in Emerging Technologies, Nagpur, India, 2024, pp. 1–7.

A. Parikh, H. Parikh, K. Patel, N. Bhatt, and P. Praiapati, "Number Plate Detection and Recognition Using OpenCV," in 2024 2nd International Conference on Intelligent Data Communication Technologies and Internet of Things, Bengaluru, India, 2024, pp. 1460–1467.

V. Devisurya, S. Adil Mohamed, A. Gavin, and A. Kamal, "Enhanced Number Plate Recognition for Restricted Area Access Control Using Deep Learning Models and EasyOCR Integration," in 2024 3rd International Conference on Artificial Intelligence For Internet of Things, Vellore, India, 2024, pp. 1–6.

I. J. Khan, Md. F. Bin Amin, M. H. Sabbir, D. M. Nejhum, A. H. Muhammad Nanzil, and R. Rahman, "Vehicle Number Plate Detection and Encryption in Digital Images Using YOLOv8 and Chaotic-Based Encryption Scheme," in 2024 6th International Conference on Electrical Engineering and Information & Communication Technology, Dhaka, Bangladesh, 2024, pp. 717–722.

G. Jocher, J. Qiu, and A. Chaurasia, "Ultralytics YOLO11," Ultralytics YOLO Docs. https://github.com/ultralytics/ultralytics.

A. Wanto, Y. Yuhandri, and O. Okfalisa, "Optimization Accuracy of CNN Model by Utilizing CLAHE Parameters in Image Classification Problems," in 2023 International Conference on Networking, Electrical Engineering, Computer Science, and Technology, Bandar Lampung, Indonesia, 2023, pp. 253–258.

M. Widyaningsih, T. K. Priyambodo, M. E. Wibowo, and M. Kamal, "Optimization Contrast Enhancement and Noise Reduction for Semantic Segmentation of Oil Palm Aerial Imagery," International Journal of Intelligent Engineering and Systems, vol. 16, no. 1, pp. 597–609, Feb. 2023.

R. A. Pramunendar, D. P. Prabowo, D. Pergiwati, Y. Sari, P. N. Andono, and M. A. Soeleman, "New Workflow for Marine Fish Classification Based on Combination Features and CLAHE Enhancement Technique," International Journal of Intelligent Engineering and Systems, vol. 13, no. 4, pp. 293–304, Aug. 2020.

A. Ghosh, "YOLO11: Faster Than You Can Imagine!,"LearnOpenCV. https://learnopencv.com/yolo11/.

N. Sajitha and S. P. Priya, "Optimal Artificial Neural Network-based Fabric Defect Detection and Classification," Engineering, Technology & Applied Science Research, vol. 14, no. 2, pp. 13148–13152, Apr. 2024.

K. Zuiderveld, "Contrast limited adaptive histogram equalization," in Graphics gems IV, P. S. Heckbert, Ed. San Diego, CA, USA: Academic Press Professional, Inc., 1994, pp. 474–485.

A. M. Reza, "Realization of the Contrast Limited Adaptive Histogram Equalization (CLAHE) for Real-Time Image Enhancement," Journal of VLSI signal processing systems for signal, image and video technology, vol. 38, no. 1, pp. 35–44, Aug. 2004.

R. Padilla, S. L. Netto, and E. A. B. da Silva, "A Survey on Performance Metrics for Object-Detection Algorithms," in 2020 International Conference on Systems, Signals and Image Processing, Niteroi, Brazil, 2020, pp. 237–242.

Sutikno, A. Sugiharto, and R. Kusumaningrum, "Automated Detection of Driver and Passenger Without Seat Belt using YOLOv8," International Journal of Advanced Computer Science and Applications, vol. 14, no. 11, pp. 806–813, 2023.

H. J. Farell, K. J. Mudita, and R. Sutoyo, "Automatic Number Plate Recognition Performance Comparison in Old and New Indonesian License Plates Using Deep Learning," ICIC Express Letters, vol. 18, no. 8, pp. 793–799, Aug. 2024.

A. Srivastava, P. Narote, S. Fatangare, S. Kakade, and R. Kulkarni, "Automatic Number Plate Detection System for Indian Vehicles Using Yolov5 and EasyOCR," in Proceedings of the 12th International Conference on Soft Computing for Problem Solving, Roorkee, India, 2024, pp. 305–314.

A. Naureen, K. C. Krishna, N. S. Teja, L. Mahesh, and K. Vamshi, "College Bus Number Plate Registration Detection Using YOLO-V8," in 2023 International Conference on Evolutionary Algorithms and Soft Computing Techniques, Bengaluru, India, 2023, pp. 1–7.

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How to Cite

[1]
Sutikno, ., Sugiharto, A. and Kusumaningrum, R. 2025. Enhanced Automatic License Plate Detection and Recognition using CLAHE and YOLOv11 for Seat Belt Compliance Detection. Engineering, Technology & Applied Science Research. 15, 1 (Feb. 2025), 20271–20278. DOI:https://doi.org/10.48084/etasr.9629.

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