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Machine learning algorithms application to road defects classification

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 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...

Теги: a random forest algorithm , boosting algorithm , graph-cuts method , markov random fields , pavement condition , road defects , adaptive boosting , artificial intelligence , decision trees , defects , feature extraction , graphic methods , image segmentation , learnin
Раздел: ИСЭМ СО РАН
A robust approach for road pavement defects detection and classification

Nguyen T.H., Nguyen T.L., Sidorov D.N. A robust approach for road pavement defects detection and classification // Journal of Computational and Engineering Mathematics. Vol.3. No.3. 2016. P.40-52. DOI: 10.14529/jcem160305. The objective of this paper is to propose a robust approach to building a computer vision system to detect and classify pavement defects based on features, such as the contour of feature (chain code histogram, Hu-moment), the shape of an object (length, width, area). In this paper...

Теги: feature extraction , defect pavement , defects detection , markov random fields , graph cut , random forests , computer vision
Раздел: ИСЭМ СО РАН


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