Journal article Open Access

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

Francisco Bonnin-Pascual; Alberto Ortiz


DCAT Export

<?xml version='1.0' encoding='utf-8'?>
<rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:adms="http://www.w3.org/ns/adms#" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:dct="http://purl.org/dc/terms/" xmlns:dctype="http://purl.org/dc/dcmitype/" xmlns:dcat="http://www.w3.org/ns/dcat#" xmlns:duv="http://www.w3.org/ns/duv#" xmlns:foaf="http://xmlns.com/foaf/0.1/" xmlns:frapo="http://purl.org/cerif/frapo/" xmlns:geo="http://www.w3.org/2003/01/geo/wgs84_pos#" xmlns:gsp="http://www.opengis.net/ont/geosparql#" xmlns:locn="http://www.w3.org/ns/locn#" xmlns:org="http://www.w3.org/ns/org#" xmlns:owl="http://www.w3.org/2002/07/owl#" xmlns:prov="http://www.w3.org/ns/prov#" xmlns:rdfs="http://www.w3.org/2000/01/rdf-schema#" xmlns:schema="http://schema.org/" xmlns:skos="http://www.w3.org/2004/02/skos/core#" xmlns:vcard="http://www.w3.org/2006/vcard/ns#" xmlns:wdrs="http://www.w3.org/2007/05/powder-s#">
  <rdf:Description rdf:about="https://doi.org/10.5281/zenodo.4408152">
    <dct:identifier rdf:datatype="http://www.w3.org/2001/XMLSchema#anyURI">https://doi.org/10.5281/zenodo.4408152</dct:identifier>
    <foaf:page rdf:resource="https://doi.org/10.5281/zenodo.4408152"/>
    <dct:creator>
      <rdf:Description rdf:about="http://orcid.org/0000-0002-8253-7455">
        <rdf:type rdf:resource="http://xmlns.com/foaf/0.1/Agent"/>
        <dct:identifier rdf:datatype="http://www.w3.org/2001/XMLSchema#string">0000-0002-8253-7455</dct:identifier>
        <foaf:name>Francisco Bonnin-Pascual</foaf:name>
        <org:memberOf>
          <foaf:Organization>
            <foaf:name>University of the Balearic Islands</foaf:name>
          </foaf:Organization>
        </org:memberOf>
      </rdf:Description>
    </dct:creator>
    <dct:creator>
      <rdf:Description rdf:about="http://orcid.org/0000-0002-4215-3764">
        <rdf:type rdf:resource="http://xmlns.com/foaf/0.1/Agent"/>
        <dct:identifier rdf:datatype="http://www.w3.org/2001/XMLSchema#string">0000-0002-4215-3764</dct:identifier>
        <foaf:name>Alberto Ortiz</foaf:name>
        <org:memberOf>
          <foaf:Organization>
            <foaf:name>University of the Balearic Islands</foaf:name>
          </foaf:Organization>
        </org:memberOf>
      </rdf:Description>
    </dct:creator>
    <dct:title>A novel approach for defect detection on vessel structures using saliency-related features</dct:title>
    <dct:publisher>
      <foaf:Agent>
        <foaf:name>Zenodo</foaf:name>
      </foaf:Agent>
    </dct:publisher>
    <dct:issued rdf:datatype="http://www.w3.org/2001/XMLSchema#gYear">2018</dct:issued>
    <dcat:keyword>Defect detection</dcat:keyword>
    <dcat:keyword>Vessel inspection</dcat:keyword>
    <dcat:keyword>Corrosion</dcat:keyword>
    <dcat:keyword>Cracks</dcat:keyword>
    <dcat:keyword>Saliency</dcat:keyword>
    <dcat:keyword>Micro-Aerial Vehicle</dcat:keyword>
    <frapo:isFundedBy rdf:resource="info:eu-repo/grantAgreement/EC/H2020/779776/"/>
    <schema:funder>
      <foaf:Organization>
        <dct:identifier rdf:datatype="http://www.w3.org/2001/XMLSchema#string">10.13039/100010661</dct:identifier>
        <foaf:name>European Commission</foaf:name>
      </foaf:Organization>
    </schema:funder>
    <frapo:isFundedBy rdf:resource="info:eu-repo/grantAgreement/EC/FP7/605200/"/>
    <schema:funder>
      <foaf:Organization>
        <dct:identifier rdf:datatype="http://www.w3.org/2001/XMLSchema#string">10.13039/100011102</dct:identifier>
        <foaf:name>European Commission</foaf:name>
      </foaf:Organization>
    </schema:funder>
    <dct:issued rdf:datatype="http://www.w3.org/2001/XMLSchema#date">2018-02-01</dct:issued>
    <owl:sameAs rdf:resource="https://zenodo.org/record/4408152"/>
    <adms:identifier>
      <adms:Identifier>
        <skos:notation rdf:datatype="http://www.w3.org/2001/XMLSchema#anyURI">https://zenodo.org/record/4408152</skos:notation>
        <adms:schemeAgency>url</adms:schemeAgency>
      </adms:Identifier>
    </adms:identifier>
    <dct:isVersionOf rdf:resource="https://doi.org/10.5281/zenodo.4408151"/>
    <dct:description>&lt;p&gt;Seagoing vessels have to undergo regular visual inspections in order to detect defects such as cracks and corrosion&amp;nbsp;before they result into catastrophic consequences. These inspections are currently performed manually by ship&amp;nbsp;surveyors at a great cost, so that any level of assistance during the inspection process by means of e.g. a fleet of&amp;nbsp;robots capable of defect detection would significatively decrease the inspection cost. In this paper, we describe a&amp;nbsp;novel framework for visually detecting the aforementioned defects. This framework is generic and flexible in the&amp;nbsp;sense that it can be easily configured to compute the features that perform better for the inspection at hand.&amp;nbsp;Making use of this framework and inspired by the idea of conspicuity, this work considers contrast and symmetry&amp;nbsp;as features for detecting defects and shows their usefulness for the case of vessels. Three different combination&amp;nbsp;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&amp;nbsp;classification rates than state of the art methods and prove its usability for images collected by a micro-aerial&amp;nbsp;robotic platform intended for visual inspection.&lt;/p&gt;</dct:description>
    <dct:description>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).</dct:description>
    <dct:accessRights rdf:resource="http://publications.europa.eu/resource/authority/access-right/PUBLIC"/>
    <dct:accessRights>
      <dct:RightsStatement rdf:about="info:eu-repo/semantics/openAccess">
        <rdfs:label>Open Access</rdfs:label>
      </dct:RightsStatement>
    </dct:accessRights>
    <dct:license rdf:resource="https://creativecommons.org/licenses/by/4.0/legalcode"/>
    <dcat:distribution>
      <dcat:Distribution>
        <dcat:accessURL rdf:resource="https://doi.org/10.5281/zenodo.4408152"/>
        <dcat:byteSize>5219296</dcat:byteSize>
        <dcat:downloadURL rdf:resource="https://zenodo.org/record/4408152/files/FBPOcEng2018.pdf"/>
        <dcat:mediaType>application/pdf</dcat:mediaType>
      </dcat:Distribution>
    </dcat:distribution>
  </rdf:Description>
  <foaf:Project rdf:about="info:eu-repo/grantAgreement/EC/H2020/779776/">
    <dct:identifier rdf:datatype="http://www.w3.org/2001/XMLSchema#string">779776</dct:identifier>
    <dct:title>Robotics Technology for Inspection of Ships</dct:title>
    <frapo:isAwardedBy>
      <foaf:Organization>
        <dct:identifier rdf:datatype="http://www.w3.org/2001/XMLSchema#string">10.13039/100010661</dct:identifier>
        <foaf:name>European Commission</foaf:name>
      </foaf:Organization>
    </frapo:isAwardedBy>
  </foaf:Project>
  <foaf:Project rdf:about="info:eu-repo/grantAgreement/EC/FP7/605200/">
    <dct:identifier rdf:datatype="http://www.w3.org/2001/XMLSchema#string">605200</dct:identifier>
    <dct:title>Inspection Capabilities for Enhanced Ship Safety</dct:title>
    <frapo:isAwardedBy>
      <foaf:Organization>
        <dct:identifier rdf:datatype="http://www.w3.org/2001/XMLSchema#string">10.13039/100011102</dct:identifier>
        <foaf:name>European Commission</foaf:name>
      </foaf:Organization>
    </frapo:isAwardedBy>
  </foaf:Project>
</rdf:RDF>
45
85
views
downloads
All versions This version
Views 4545
Downloads 8585
Data volume 443.6 MB443.6 MB
Unique views 3737
Unique downloads 8080

Share

Cite as