Show simple item record

dc.contributor.authorMarini, S.
dc.contributor.authorAzzurro, E.
dc.contributor.authorCoco, S.
dc.contributor.authorRío Fernandez, Joaquín del
dc.contributor.authorEnguídanos, S.
dc.contributor.authorFanelli, E.
dc.contributor.authorNogueras Cervera, Marc
dc.contributor.authorSbragaglia, Valerio
dc.contributor.authorToma, Daniel
dc.contributor.authorAguzzi, Jacopo
dc.date.accessioned2017-01-24T12:25:43Z
dc.date.available2017-01-24T12:25:43Z
dc.date.issued2016
dc.identifier.citationMarini, S. [et al.]. Automatic fish counting from underwater video images: performance estimation and evaluation. A: 7th International Workshop on Marine Technology : MARTECH 2016. "Instrumentation viewpoint". Vilanova i la Geltrú: SARTI, 2016, p. 55-57.
dc.identifier.issn1886-4864
dc.identifier.urihttp://hdl.handle.net/2117/99939
dc.description.abstractCabled observatories offer new opportunities to monitor species abundances at frequencies and durations never attained before. When nodes bear cameras, these may be transformed into the first sensor capable of quantifying biological activities at individual, populational, species, and community levels, if automation image processing can be sufficiently implemented. Here, we developed a binary classifier for the fish automated recognition based on Genetic Programming tested on the images provided by OBSEA EMSO testing site platform located at 20 m of depth off Vilanova i la Gertrú (Spain). The performance evaluation of the automatic classifier resulted in a 78% of accuracy compared with the manual counting. Considering the huge dimension of data provided by cabled observatories and the difficulty of manual processing, we consider this result highly promising also in view of future implementation of the methodology to increase the accuracy.
dc.format.extent3 p.
dc.language.isoeng
dc.publisherSARTI
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 Spain
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.subjectÀrees temàtiques de la UPC::Enginyeria agroalimentària::Ciències de la terra i de la vida::Zoologia
dc.subjectÀrees temàtiques de la UPC::Enginyeria de la telecomunicació::Processament del senyal::Processament de la imatge i del senyal vídeo
dc.subjectÀrees temàtiques de la UPC::Enginyeria de la telecomunicació::Processament del senyal::Reconeixement de formes
dc.subject.lcshFishes -- Counting
dc.subject.lcshFish populations -- Mediterranean Sea
dc.subject.lcshUnderwater imaging systems
dc.subject.lcshOcean bottom -- Research
dc.subject.otherCabled observatories
dc.subject.otherManual fish counts
dc.subject.otherAutomated fish counts
dc.subject.otherPattern recognition
dc.titleAutomatic fish counting from underwater video images: performance estimation and evaluation
dc.typeConference lecture
dc.subject.lemacPeixos
dc.subject.lemacObservatoris
dc.subject.lemacComunicacions subacuàtiques
dc.subject.lemacFons marins -- Investigació
dc.identifier.dlB-32814-2006
dc.description.peerreviewedPeer Reviewed
dc.rights.accessOpen Access
local.citation.contributor7th International Workshop on Marine Technology : MARTECH 2016
local.citation.pubplaceVilanova i la Geltrú
local.citation.publicationNameInstrumentation viewpoint
local.citation.number19
local.citation.startingPage55
local.citation.endingPage57


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record

Attribution-NonCommercial-NoDerivs 3.0 Spain
Except where otherwise noted, content on this work is licensed under a Creative Commons license : Attribution-NonCommercial-NoDerivs 3.0 Spain