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Πεδίο DCΤιμήΓλώσσα
dc.contributor.authorŽuži, Marek-
dc.contributor.authorČejka, Jan-
dc.contributor.authorBruno, Fabio-
dc.contributor.authorSkarlatos, Dimitrios-
dc.contributor.authorLiarokapis, Fotis-
dc.date.accessioned2019-04-07T18:39:58Z-
dc.date.available2019-04-07T18:39:58Z-
dc.date.issued2018-08-01-
dc.identifier.citationFrontiers Robotics AI, 2018, vol. 5, no. AUGen_US
dc.identifier.issn22969144-
dc.description.abstractUnderwater augmented reality is a very challenging task and amongst several issues, one of the most crucial aspects involves real-time tracking. Particles present in water combined with the uneven absorption of light decrease the visibility in the underwater environment. Dehazing methods are used in many areas to improve the quality of digital image data that is degraded by the influence of the environment. This paper describes the visibility conditions affecting underwater scenes and shows existing dehazing techniques that successfully improve the quality of underwater images. Four underwater dehazing methods are selected for evaluation of their capability of improving the success of square marker detection in underwater videos. Two reviewed methods represent approaches of image restoration: Multi-Scale Fusion, and Bright Channel Prior. Another two methods evaluated, the Automatic Color Enhancement and the Screened Poisson Equation, are methods of image enhancement. The evaluation uses diverse test data set to evaluate different environmental conditions. Results of the evaluation show an increased number of successful marker detections in videos pre-processed by dehazing algorithms and evaluate the performance of each compared method. The Screened Poisson method performs slightly better to other methods across various tested environments, while Bright Channel Prior and Automatic Color Enhancement shows similarly positive results.en_US
dc.formatpdfen_US
dc.language.isoenen_US
dc.relation.ispartofFrontiers Robotics AIen_US
dc.rights© Žuži, Čejka, Bruno, Skarlatos and Liarokapis.en_US
dc.subjectAugmented realityen_US
dc.subjectDehazingen_US
dc.subjectImage restorationen_US
dc.subjectMarkersen_US
dc.subjectTrackingen_US
dc.subjectUnderwater imagesen_US
dc.titleImpact of dehazing on underwater marker detection for augmented realityen_US
dc.typeArticleen_US
dc.collaborationMasaryk Universityen_US
dc.collaborationUniversity of Calabriaen_US
dc.collaborationCyprus University of Technologyen_US
dc.subject.categoryComputer and Information Sciencesen_US
dc.journalsOpen Accessen_US
dc.countryCzech Republicen_US
dc.countryItalyen_US
dc.countryCyprusen_US
dc.subject.fieldNatural Sciencesen_US
dc.publicationPeer Revieweden_US
dc.identifier.doi10.3389/frobt.2018.00092en_US
dc.relation.issueAUGen_US
dc.relation.volume5en_US
cut.common.academicyear2017-2018en_US
item.fulltextWith Fulltext-
item.languageiso639-1en-
item.grantfulltextopen-
item.openairecristypehttp://purl.org/coar/resource_type/c_6501-
item.cerifentitytypePublications-
item.openairetypearticle-
crisitem.journal.journalissn2296-9144-
crisitem.journal.publisherFrontiers-
crisitem.author.deptDepartment of Civil Engineering and Geomatics-
crisitem.author.deptDepartment of Civil Engineering and Geomatics-
crisitem.author.facultyFaculty of Engineering and Technology-
crisitem.author.facultyFaculty of Engineering and Technology-
crisitem.author.orcid0000-0002-2732-4780-
crisitem.author.orcid0000-0003-3617-2261-
crisitem.author.parentorgFaculty of Engineering and Technology-
crisitem.author.parentorgFaculty of Engineering and Technology-
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