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Publication . Article . 2018

A novel approach for defect detection on vessel structures using saliency-related features

Bonnin-Pascual, Francisco; Ortiz, Alberto;
Open Access
English
Published: 01 Feb 2018 Journal: Ocean Engineering, volume 149, pages 397-408 (issn: 00298018, Copyright policy )
Abstract

Seagoing vessels have to undergo regular visual inspections in order to detect defects such as cracks and corrosion before they result into catastrophic consequences. These inspections are currently performed manually by ship surveyors at a great cost, so that any level of assistance during the inspection process by means of e.g. a fleet of robots capable of defect detection would significatively decrease the inspection cost. In this paper, we describe a novel framework for visually detecting the aforementioned defects. This framework is generic and flexible in the sense that it can be easily configured to compute the features that perform better for the inspection at hand. Making use of this framework and inspired by the idea of conspicuity, this work considers contrast and symmetry as features for detecting defects and shows their usefulness for the case of vessels. Three different combination operators are additionally tested in order to merge the information provided by these features and improve the detection performance. Experimental results for different configurations of the detection framework show better classification rates than state of the art methods and prove its usability for images collected by a micro-aerial robotic platform intended for visual inspection.

This is a preprint version of publication with DOI: https://doi.org/10.1016/j.oceaneng.2017.08.024. This work is partially supported by FEDER funding, by project nr. AAEE50/2015 (Direccio General d'Innovacio i Recerca, Govern de les Illes Balears).

Subjects by Vocabulary

Microsoft Academic Graph classification: Artificial intelligence business.industry business Robot Visual inspection Computer vision Usability Detection performance Merge (version control) Engineering

ACM Computing Classification System: GeneralLiterature_MISCELLANEOUS

Subjects

Ocean Engineering, Environmental Engineering, Defect detection, Vessel inspection, Corrosion, Cracks, Saliency, Micro-Aerial Vehicle

Related Organizations
Funded by
EC| ROBINS
Project
ROBINS
Robotics Technology for Inspection of Ships
  • Funder: European Commission (EC)
  • Project Code: 779776
  • Funding stream: H2020 | IA
Validated by funder
,
EC| INCASS
Project
INCASS
Inspection Capabilities for Enhanced Ship Safety
  • Funder: European Commission (EC)
  • Project Code: 605200
  • Funding stream: FP7 | SP1 | TPT
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Ocean Engineering
Article
License: cc-by
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