Publié en ligne: 01 déc. 2016
Pages: 2069 - 2087
Reçu: 27 juil. 2016
Accepté: 19 oct. 2016
DOI: https://doi.org/10.21307/ijssis-2017-953
Mots clés
© 2016 J. H. Song et al., published by Sciendo
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
Aiming at the problem of automatic identification and evaluation of road damage degree, the road damage identification and degree assessment algorithms based on unmanned vehicles experimental platform are studied. The road crack segmentation extraction method based on adaptive sliding window is studied. On this basis, the road damage crack classifies and identifies according to the crack geometry information and the principle of template matching. The road damage degree assessment algorithm based on fuzzy decision is proposed based on the quantitative analysis of the road crack and the corresponding parameters information. The experimental results demonstrate that the road damage identification and degree assessment algorithms proposed in this paper are effective and stable.