Michał Wyczałek

Asphalt surfaced pavement cracks detection based on histograms of oriented gradients

Cracks are the most requiring type of pavement distresses to detect and classify automatically. Due to its nature are easily absorbed by other types of pavement surface damages. Moreover, the diversity of pavement surface makes the image detection system requiring efficient computer algorithms. The paper presents the solutions tested on surface distress data which were collected automatically using downward facing cameras placed orthogonally to road pavement axis. Presented results focus on the crack-type pavement distresses. The achieved accuracy of the transverse, longitudinal and meshing cracks recognition based on the initial dataset prepared especially for this system, show it has very good chances to work efficiently with large image datasets collected during the inspection car runs.

Road structure analysis based on cross-section images processing

Road pavement structure analysis provides important information for road maintenance and renovation planning. Image processing methods applying to cross-section of the asphalt pavement can provide valuable information about the pavement structure and its quality. The paper presents a method to analyze a picture of a cross-section sample, taking into account aggregates size. The features that have been captured and quantified using 2-D images were limited to aggregates size. The elaborated algorithm and its implementation are presented. The tool is prepared as a part of a bigger system dedicated to road pavement analysis.