The internal inspection of large pipeline infrastructures, such as sewers and waterworks, is a fundamental task for the prevention of possible failures. In particular, visual inspection is typically performed by human operators on the basis of video sequences either acquired on-line or recorded for further off-line analysis. In this work, we propose a vision-based software approach to assist the human operator by conveniently showing the acquired data and by automatically detecting and highlighting the pipeline sections where relevant anomalies could occur.

A vision-based system for internal pipeline inspection

Claudio Piciarelli
;
Danilo Avola;Gian Luca Foresti
2019-01-01

Abstract

The internal inspection of large pipeline infrastructures, such as sewers and waterworks, is a fundamental task for the prevention of possible failures. In particular, visual inspection is typically performed by human operators on the basis of video sequences either acquired on-line or recorded for further off-line analysis. In this work, we propose a vision-based software approach to assist the human operator by conveniently showing the acquired data and by automatically detecting and highlighting the pipeline sections where relevant anomalies could occur.
File in questo prodotto:
File Dimensione Formato  
tii.pdf

accesso aperto

Descrizione: versione pre-print
Tipologia: Documento in Pre-print
Licenza: Creative commons
Dimensione 1.93 MB
Formato Adobe PDF
1.93 MB Adobe PDF Visualizza/Apri
tii (1).pdf

Open Access dal 07/06/2021

Descrizione: Versione post-print
Tipologia: Documento in Post-print
Licenza: Creative commons
Dimensione 10.23 MB
Formato Adobe PDF
10.23 MB Adobe PDF Visualizza/Apri
08477037.pdf

non disponibili

Descrizione: Versione editoriale
Tipologia: Versione Editoriale (PDF)
Licenza: Non pubblico
Dimensione 3.75 MB
Formato Adobe PDF
3.75 MB Adobe PDF   Visualizza/Apri   Richiedi una copia

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/11390/1139294
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 72
  • ???jsp.display-item.citation.isi??? 66
social impact