Automatic Road Pavement Assessment with Image Processing: Review and Comparison

TLDR

The paper reviews image‑processing tools for detecting cracks on French national roads and proposes a new evaluation protocol for fine‑defect detection. The method uses multi‑scale feature extraction followed by Markovian segmentation to detect pavement cracks. The approach was validated and shown to outperform a morphological‑tool baseline in crack detection.

Abstract

In the field of noninvasive sensing techniques for civil infrastructures monitoring, this paper addresses the problem of crack detection, in the surface of the French national roads, by automatic analysis of optical images. The first contribution is a state of the art of the image-processing tools applied to civil engineering. The second contribution is about fine-defect detection in pavement surface. The approach is based on a multi-scale extraction and a Markovian segmentation. Third, an evaluation and comparison protocol which has been designed for evaluating this difficult task—the road pavement crack detection—is introduced. Finally, the proposed method is validated, analysed, and compared to a detection approach based on morphological tools.