Image based road condition estimation

Municipalities and Cities face many challenges with infrastructure management. Various assets like traffic signs and the road network need to be maintained.

With the accessibility of mobil cameras like smartphones and modern computer vision algorithms it is now possible to gather and evaluate large amounts of images.

This project focuses on evaluating the road condition based on smartphone images and making this information accessible in a web system. The next steps focus on summarizing the gathered information for a given time interval. Additionally we are aiming to detect, analyze and predict changes in the future condition of the road network.

Publications


2025
Konzeption und Parametrierung von Algorithmen zur Abbildung von Veränderungen in unstrukturierten Bilddaten. PhD dissertation
Münke, F. R.
2025, June 17. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000182373
2024
Adaptable Accelerometer Signal Processing Pipelines for Smartphone based Evenness Estimation
Münke, F. R.; Schenk, M.; Murr, S.; Reischl, M.
2024. Journal of Signal Processing Systems, 96 (10), 617–626. doi:10.1007/s11265-024-01939-2
A Review of Adaptable Conventional Image Processing Pipelines and Deep Learning on limited Datasets
Münke, F. R.; Schützke, J.; Berens, F.; Reischl, M.
2024. Machine vision and applications, 35, Article no: 25. doi:10.1007/s00138-023-01501-3
Accelerating Materials Discovery: Automated Identification of Prospects from X‐Ray Diffraction Data in Fast Screening Experiments
Schuetzke, J.; Schweidler, S.; Muenke, F. R.; Orth, A.; Khandelwal, A. D.; Breitung, B.; Aghassi-Hagmann, J.; Reischl, M.
2024. Advanced Intelligent Systems, 6 (3), Art.-Nr.: 2300501. doi:10.1002/aisy.202300501
Completed Project