AUTOMATED DETECTION AND VECTORIZATION OF ROAD ELEMENTS IN HIGH RESOLUTION ORTHOGRAPHIC IMAGES

Abstract

This paper proposes, describes, and applies an algorithm for the automatic detection of selected elements of road infrastructure, along with the option to determine their spatial information. The principle is based on the evaluation of the color spectrum of the selected object on orthographic images. As a source image used for the processing, output from low-altitude aerial photogrammetry or terrestrial laser scanning can be used, together with the option to implement digital elevation models into the processing. The approach is based on the detection of the color composition of the selected element of the road, followed by clustering of the identified elements within the image and mathematical transformation of the clusters into a spatial vector form. Prior to the processing, the target objects are filtered out based on user input, for which vectorization is performed. The outputs are in the form of contours or the determined basic structure of the object. The main difference compared to existing methods is that the vectorization is only performed on the selected, pre-filtered parts of the raster image with identified target objects, not the whole image. This approach makes it possible to effectively and automatically identify and analyze, e.g., the edge of the road, road markings, or road features. This enables the subsequent implementation of the identified outputs into more complex spatial models of the road or its proximity. Additionally, the processing of the data to create a digital model of the environment can be automated, with a significant saving of time and related costs.