CUED Publications database

Pothole detection in asphalt pavement images

Koch, C and Brilakis, I (2011) Pothole detection in asphalt pavement images. Advanced Engineering Informatics, 25. pp. 507-515. ISSN 1474-0346

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Pavement condition assessment is essential when developing road network maintenance programs. In practice, the data collection process is to a large extent automated. However, pavement distress detection (cracks, potholes, etc.) is mostly performed manually, which is labor-intensive and time-consuming. Existing methods either rely on complete 3D surface reconstruction, which comes along with high equipment and computation costs, or make use of acceleration data, which can only provide preliminary and rough condition surveys. In this paper we present a method for automated pothole detection in asphalt pavement images. In the proposed method an image is first segmented into defect and non-defect regions using histogram shape-based thresholding. Based on the geometric properties of a defect region the potential pothole shape is approximated utilizing morphological thinning and elliptic regression. Subsequently, the texture inside a potential defect shape is extracted and compared with the texture of the surrounding non-defect pavement in order to determine if the region of interest represents an actual pothole. This methodology has been implemented in a MATLAB prototype, trained and tested on 120 pavement images. The results show that this method can detect potholes in asphalt pavement images with reasonable accuracy.

Item Type: Article
Uncontrolled Keywords: Pavement assessment Pothole detection Visual sensing Image processing
Divisions: Div D > Construction Engineering
Depositing User: Cron Job
Date Deposited: 17 Jul 2017 19:17
Last Modified: 22 Jun 2018 20:30