A simplified computer vision system for road surface inspection and maintenance

Quintana González, Marcos and Torres Arjona, Juan and Menendez Garcia, Jose Manuel (2016). A simplified computer vision system for road surface inspection and maintenance. "IEEE Transactions on Intelligent Transportation Systems", v. 17 (n. 3); pp. 608-619. ISSN 1524-9050. https://doi.org/10.1109/TITS.2015.2482222.

Description

Title: A simplified computer vision system for road surface inspection and maintenance
Author/s:
  • Quintana González, Marcos
  • Torres Arjona, Juan
  • Menendez Garcia, Jose Manuel
Item Type: Article
Título de Revista/Publicación: IEEE Transactions on Intelligent Transportation Systems
Date: March 2016
Volume: 17
Subjects:
Freetext Keywords: Road safety, computer vision, pattern recognition, image processing.
Faculty: E.T.S.I. Telecomunicación (UPM)
Department: Señales, Sistemas y Radiocomunicaciones
Creative Commons Licenses: Recognition - No derivative works - Non commercial

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Abstract

This paper presents a computer vision system whose aim is to detect and classify cracks on road surfaces. Most of the previous works consisted of complex and expensive acquisition systems, whereas we have developed a simpler one composed by a single camera mounted on a light truck and no additional illumination. The system also includes tracking devices in order to geolocalize the captured images. The computer vision algorithm has three steps: hard shoulder detection, cell candidate proposal, and crack classification. First the region of interest (ROI) is delimited using the Hough transform (HT) to detect the hard shoulders. The cell candidate step is divided into two substeps: Hough transform features (HTF) and local binary pattern (LBP). Both of them split up the image into nonoverlapping small grid cells and also extract edge orientation and texture features, respectively. At the fusion stage, the detection is completed by mixing those techniques and obtaining the crack seeds. Afterward, their shape is improved using a new developed morphology operator. Finally, one classification based on the orientation of the detected lines has been applied following the Chain code. Massive experiments were performed on several stretches on a Spanish road showing very good performance.

More information

Item ID: 46145
DC Identifier: http://oa.upm.es/46145/
OAI Identifier: oai:oa.upm.es:46145
DOI: 10.1109/TITS.2015.2482222
Official URL: http://ieeexplore.ieee.org/document/7297863/
Deposited by: Memoria Investigacion
Deposited on: 03 Jun 2017 11:52
Last Modified: 03 Jun 2017 11:52
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