Image-based modeling (IBM) is a well-known technique to obtain high quality 3D models based on multi view images. IBM started being used in several applications such as inspection, identification of objects and visualization, due to the user-friendly approach, the low cost and highly automated technique. This paper focuses on the investigation of the potential application of IBM in the diagnosis of road pavement distresses and in particular rutting. Indeed, the evaluation of the rutting distress is a fundamental step to define the whole state of a pavement as demonstrated by the calculation of Present Serviceability Index (PSI). Currently, the permanent deformation is measured monitoring visually the rut depth with the approximations that this procedure involves. Nevertheless, the exact measure of the rut depth is necessary to evaluate precisely the cause and the severity of this distress and be effective in the maintenance and rehabilitation of the pavement structure. The objective of this study is to apply the IBM technique on a laboratory rutted sample, in order to verify the accuracy of the method in determining the rut depth. To achieve this, a comparison has been made between the 3D model obtained with IBM and the one obtained with blue led 3D scan (Artec Spider) of the same rutted asphalt concrete. The metric accuracy of the model is then defined and its validity is assessed, in terms of distress diagnosis.

Inzerillo, L., Di Mino, G., Bressi, S., Di Paola, F., Noto, S. (2016). Image Based Modeling Technique for Pavement Distress surveys: a Specific Application to Rutting. INTERNATIONAL JOURNAL OF ENGINEERING & TECHNOLOGY, International Journal of Engineering & Technology IJET-IJENS Vol:16 No:05(5), 1-9.

Image Based Modeling Technique for Pavement Distress surveys: a Specific Application to Rutting

INZERILLO, Laura;DI MINO, Gaetano;BRESSI, SARA;DI PAOLA, Francesco;NOTO, Silvia
2016-01-01

Abstract

Image-based modeling (IBM) is a well-known technique to obtain high quality 3D models based on multi view images. IBM started being used in several applications such as inspection, identification of objects and visualization, due to the user-friendly approach, the low cost and highly automated technique. This paper focuses on the investigation of the potential application of IBM in the diagnosis of road pavement distresses and in particular rutting. Indeed, the evaluation of the rutting distress is a fundamental step to define the whole state of a pavement as demonstrated by the calculation of Present Serviceability Index (PSI). Currently, the permanent deformation is measured monitoring visually the rut depth with the approximations that this procedure involves. Nevertheless, the exact measure of the rut depth is necessary to evaluate precisely the cause and the severity of this distress and be effective in the maintenance and rehabilitation of the pavement structure. The objective of this study is to apply the IBM technique on a laboratory rutted sample, in order to verify the accuracy of the method in determining the rut depth. To achieve this, a comparison has been made between the 3D model obtained with IBM and the one obtained with blue led 3D scan (Artec Spider) of the same rutted asphalt concrete. The metric accuracy of the model is then defined and its validity is assessed, in terms of distress diagnosis.
2016
Inzerillo, L., Di Mino, G., Bressi, S., Di Paola, F., Noto, S. (2016). Image Based Modeling Technique for Pavement Distress surveys: a Specific Application to Rutting. INTERNATIONAL JOURNAL OF ENGINEERING & TECHNOLOGY, International Journal of Engineering & Technology IJET-IJENS Vol:16 No:05(5), 1-9.
File in questo prodotto:
File Dimensione Formato  
Image based modeling technique for pavement distress surveys.pdf

accesso aperto

Descrizione: Full paper
Dimensione 959.27 kB
Formato Adobe PDF
959.27 kB Adobe PDF Visualizza/Apri

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10447/213313
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus ND
  • ???jsp.display-item.citation.isi??? ND
social impact