Detection Of Road Surface Defects From Data Acquired By A Laser Scanner

Abstract

Research in the field of automatic detection of road surface defects has been relativelywidespread in recent years. Most of the existing works solve this issue by processing the imageacquired by camera technology. The contribution of this study is the proposal of the LRS-CNN algorithmfor the detection of defects on road surfaces based on their laser scans. The advantage ofLRS-CNN is the ability to detect so-called microcracks, which can not be recognized from camerarecordings. We have also found that transfer learning methods are not suitable for the use of road defectdetection from their laser scans. Our LRS-CNN algorithm has been trained on unique nonpublicdata and is able to achieve up to 99.33% of success depending on the type of task.