Monitoring of Rail Line Using Multi-Sensor Camera and Correlation Filters
Student: Kehinde Waliyu Taiwo (Project, 2025)
Department of Computer Engineering
Osun State Polytechnic, Iree, Osun State
Abstract
This project ABSTRACT This project presents a rail line monitoring system using multi-sensor cameras and correlation filters to enhance railway safety. The system combines RGB, thermal, and infrared imaging to detect surface and subsurface anomalies in real-time. Correlation filters enable accurate defect detection and localization, with outputs including visual reports, GPS mapping, and maintenance recommendations. Performance evaluations show high accuracy and robustness, though challenges like initial costs and environmental sensitivities exist. The scalable design supports diverse rail networks, offering a significant improvement over traditional methods while paving the way for predictive maintenance and broader infrastructure applications.
Keywords
For the full publication, please contact the author directly at: taiwowaliyu56@gmail.com
Filters
Institutions
- Covenant Polytechnic, Aba, Abia State 1
- Covenant University, Canaan Land, Ota, Ogun State 4
- Crawford University of Apostolic Faith Mission Faith City, Igbesa, Ogun State 2
- Crescent University, Abeokuta, Ogun State 1
- Cross Rivers University of Technology, Calabar, Cross Rivers State 142
- Delta State Polytechnic, Ogwashi-Uku, Delta State 11
- Delta State Polytechnic, Otefe, Delta State 12
- Delta State University, Abraka, Delta State 138
- Ebonyi State University, Abakaliki, Ebonyi State 17
- Edo University, Iyamho, Edo State 10