A simplified computer vision system for road surface inspection and maintenance

Quintana González, Marcos; Torres Arjona, Juan y 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.

Descripción

Título: A simplified computer vision system for road surface inspection and maintenance
Autor/es:
  • Quintana González, Marcos
  • Torres Arjona, Juan
  • Menendez Garcia, Jose Manuel
Tipo de Documento: Artículo
Título de Revista/Publicación: IEEE Transactions on Intelligent Transportation Systems
Fecha: Marzo 2016
Volumen: 17
Materias:
Palabras Clave Informales: Road safety, computer vision, pattern recognition, image processing.
Escuela: E.T.S.I. Telecomunicación (UPM)
Departamento: Señales, Sistemas y Radiocomunicaciones
Licencias Creative Commons: Reconocimiento - Sin obra derivada - No comercial

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Resumen

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.

Más información

ID de Registro: 46145
Identificador DC: http://oa.upm.es/46145/
Identificador OAI: oai:oa.upm.es:46145
Identificador DOI: 10.1109/TITS.2015.2482222
URL Oficial: http://ieeexplore.ieee.org/document/7297863/
Depositado por: Memoria Investigacion
Depositado el: 03 Jun 2017 11:52
Ultima Modificación: 03 Jun 2017 11:52
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