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
- Landmark University, Omu-Aran, Kwara State 1
- Lead City University, Ibadan, Oyo State 1
- Lens Polytechnic, offa, Kwara State. 215
- Madonna University, Elele, Rivers State 20
- Madonna University, Okija, Anambra State 2
- Mcpherson University, Seriki Sotayo, Ogun State 1
- Michael and Cecilia Ibru University, Owhrode, Delta State 1
- Michael Okpara University of Agriculture, Umudike 43
- Michael Otedola Col of Primary Educ. Epe, Lagos (affl To University of Ibadan) 8
- Modibbo Adama University, Yola, Adamawa State 15