Next Article in Journal
Automatic Classification of Gait Patterns in Cerebral Palsy Patients
Previous Article in Journal
Hybrid Wind–Solar–Fuel Cell–Battery Power System with PI Control for Low-Emission Marine Vessels in Saudi Arabia
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Automation
Volume 6
Issue 4
10.3390/automation6040070
automation-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
This is an early access version, the complete PDF, HTML, and XML versions will be available soon.
Article

Evaluation of Pavement Marking Damage Degree Based on Rotating Target Detection in Real Scenarios

by
Zheng Wang
*,
Ryojun Ikeura
*,
Soichiro Hayakawa
and
Zhiliang Zhang
Faculty of Engineering, Mie University, Tsu 514-8507, Mie, Japan
*
Authors to whom correspondence should be addressed.
Automation 2025, 6(4), 70; https://doi.org/10.3390/automation6040070 (registering DOI)
Submission received: 16 September 2025 / Revised: 24 October 2025 / Accepted: 7 November 2025 / Published: 9 November 2025
(This article belongs to the Section Robotics and Autonomous Systems)
Versions Notes

Abstract

Damaged road markings are widespread, and timely detection and repair of severely damaged areas is critical to the maintenance of transport infrastructure. This study proposes a method for detecting the degree of marking damage based on the top view perspective. The method improves the minimum outer rectangle detection algorithm through pavement data enhancement and multi-scale feature fusion detection head, and establishes mathematical models of different types of markings and their minimum outer rectangles to achieve accurate detection of the degree of marking damage. The experimental results show that the improved minimum bounding rectangle detection method achieves an mAP of 97.4%, which is 4.5% higher than that of the baseline model, and the minimum error in the detection of the degree of marking damage reaches 0.54%. The experimental data verified the simplicity and efficiency of the proposed method, providing important technical support for realizing large-scale road repair and maintenance in the future.
Keywords: road marking inspection; quality evaluation; degree of deterioration inspection; rotating target inspection road marking inspection; quality evaluation; degree of deterioration inspection; rotating target inspection

Share and Cite

MDPI and ACS Style

Wang, Z.; Ikeura, R.; Hayakawa, S.; Zhang, Z. Evaluation of Pavement Marking Damage Degree Based on Rotating Target Detection in Real Scenarios. Automation 2025, 6, 70. https://doi.org/10.3390/automation6040070

AMA Style

Wang Z, Ikeura R, Hayakawa S, Zhang Z. Evaluation of Pavement Marking Damage Degree Based on Rotating Target Detection in Real Scenarios. Automation. 2025; 6(4):70. https://doi.org/10.3390/automation6040070

Chicago/Turabian Style

Wang, Zheng, Ryojun Ikeura, Soichiro Hayakawa, and Zhiliang Zhang. 2025. "Evaluation of Pavement Marking Damage Degree Based on Rotating Target Detection in Real Scenarios" Automation 6, no. 4: 70. https://doi.org/10.3390/automation6040070

APA Style

Wang, Z., Ikeura, R., Hayakawa, S., & Zhang, Z. (2025). Evaluation of Pavement Marking Damage Degree Based on Rotating Target Detection in Real Scenarios. Automation, 6(4), 70. https://doi.org/10.3390/automation6040070

Article Metrics

Back to TopTop