Research Objective No. 3 – Automatic Detection and Vectorization of Transport Infrastructure Elements from Raster Orthophotos

This research objective focuses on the development and testing of a tool for the automatic detection of selected transport infrastructure elements, including the determination of their spatial and elevation coordinates. The main outcome will be a testing interface for an algorithm designed to automate the processing of heterogeneous datasets used in creating digital environment models, achieving significant time and cost savings while improving quality and accuracy compared to manual processing. The resulting models will be applicable, for example, in traffic simulators and other applications using virtual terrain models. The approach is based on high-resolution raster orthophotos acquired through aerial photogrammetry and ground-based 3D scanning, with additional testing of alternative imaging technologies and low-quality input data to assess robustness and associated risks. Methodologically, the system detects specific pixel color patterns representing selected road infrastructure elements, clusters and identifies them within the image, and converts raster data into vector format. The innovative aspect lies in performing automated vectorization only on selected image regions containing key objects rather than processing the entire raster image. The algorithm will be calibrated and validated on an extensive dataset, including error identification and refinement. The expected outcome is an optimized, efficient solution that minimizes time delays and additional costs in the creation of digital road environment models.