This paper presents a novel intelligent system forthe automatic visual inspection of vessels consisting of three processing levels: (a) data acquisition: images are collectedusing a magnetic climbing robot equipped with a low-costmonocular camera for hull inspection; (b) feature extraction: all the images are characterized by 12 features consisting ofcolor moments in each channel of the HSV space; (c) classification: a novel tool, based on an ensemble of classifiers, is proposed to classify sub-images as rust or non-rust. This paper provides a helpful roadmap to guide future research on the detection of rusting of metals using image processing.

A vision-based system for robotic inspection of marine vessels

Rosalia Maglietta;Annalisa Milella;Massimo Caccia;Gabriele Bruzzone
2018

Abstract

This paper presents a novel intelligent system forthe automatic visual inspection of vessels consisting of three processing levels: (a) data acquisition: images are collectedusing a magnetic climbing robot equipped with a low-costmonocular camera for hull inspection; (b) feature extraction: all the images are characterized by 12 features consisting ofcolor moments in each channel of the HSV space; (c) classification: a novel tool, based on an ensemble of classifiers, is proposed to classify sub-images as rust or non-rust. This paper provides a helpful roadmap to guide future research on the detection of rusting of metals using image processing.
2018
Istituto di Studi sui Sistemi Intelligenti per l'Automazione - ISSIA - Sede Bari
Istituto di Sistemi e Tecnologie Industriali Intelligenti per il Manifatturiero Avanzato - STIIMA (ex ITIA)
Istituto di iNgegneria del Mare - INM (ex INSEAN)
Image processing
segmentation
classification
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/328146
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