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.
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