Machine learning algorithms application to road defects classification
The novel approach for automatic detection and classification of road defects is proposed based on shape and texture features analysis. The system includes three main steps: defects position detection, feature contour extraction followed by classification of defects. The proposed approach is implemented in Matlab for automatic detection and classification of defects based on digital images analysis combined with machine learning algorithms such as the random forest algorithm and boosting. Segmentation is implemented using graph-cuts method and Markov random fields. The efficiency of proposed approach is demonstrated on the real data set. © 2018 - IOS Press and the authors. All rights reserved.
Библиографическая ссылка
Nguyen T.H., Nguyen T.L., Sidorov D.N., Dreglea A.I. Machine learning algorithms application to road defects classification // Intelligent Decision Technologies. Vol.12. №1. 2018. P.59-66. DOI: 10.3233/IDT-170323
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