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Road Crack Detection using Support Vector Machine (SVM) and OTSU Algorithm
Yuslena Sari (*a), Andrean Rezky Baskara(b), Puguh Budi Prakoso(c)

(a) Department of Information Technology, Faculty of Engineering Universitas Lambung Mangkurat
National Center for Sustainable Transportation Technology, Indonesia Banjarmasin, Indonesia
yuzlena[at]ulm.ac.id
(b) Department of Information Technology, Faculty of Engineering Universitas Lambung Mangkurat
National Center for Sustainable Transportation Technology, Indonesia Banjarmasin, Indonesia
andreyan.baskaraa[at]ulm.ac.id
(c) Department of Civil Engineering, Faculty of Engineering Universitas Lambung Mangkurat,
National Center for Sustainable Transportation Technology, Indonesia
Banjarmasin, Indonesia
puguh.prakoso[at]ulm.ac.id


Abstract

Cracks are one type of pavement surface damages, whose assessment is very important for developing road network maintenance strategies, which aims to ensure the functioning of the road and driving safety. Existing methods for automatic crack detection depend mostly on expensive equipment and high maintenance and cannot divide the crack segments accurately. This paper discusses an automation method of classification and segmentation of asphalt pavement cracks. The goal of the research is to classify asphalt pavement cracks using the classification method of the Support Vector Machine (SVM) algorithm and segmentation method of the OTSU algorithm. The OTSU algorithm for segmentation has advantages in choosing the optimal threshold that is stable. This algorithm is proven to be more effective and stronger than conventional segmentation algorithms. For detection results, the proposed method achieves overall accuracy.

Keywords: crack; SVM; segmentation; OTSU

Topic: Transportation Safety

Link: https://ifory.id/abstract/rEaWLyFzM3QR

Conference: The 6th International Conference on Electric Vehicular Technology (ICEVT 2019)

Plain Format | Corresponding Author (Yuslena Sari)

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