Repository logo
 
Publication

Cloud and clear sky pixel classification in ground-based all-sky hemispherical digital images

dc.contributor.authorFerreira, P. M.
dc.contributor.authorMartins, I.
dc.contributor.authorRuano, Antonio
dc.date.accessioned2013-01-29T14:39:50Z
dc.date.available2013-01-29T14:39:50Z
dc.date.issued2010
dc.date.updated2013-01-26T16:58:11Z
dc.description.abstractCloudiness is the non-predictable factor most a ecting the solar radiation reaching a particular location on the Earth surface. Therefore it has great impact on the performance of predictive solar radiation models for that location. This work represents one step towards the improvement of such models by using ground-to-sky hemispherical colour digital images as a means to estimate the fraction of visible sky corresponding to clouds and to clear sky. The general approach, common to many image processing applications, consists in finding one threshold on a given pixel intensity scale that segments the image pixels into clear sky and cloud. In order to allow the evaluation and comparison of image thresholding methods, the pixels of 410 images were manually classified as clear sky or cloud, establishing a reference database. Two well known image thresholding algorithms are tested and a neural network approach is presented. For the latter, a number of statistical measures is extracted from the images constituting a feature space of potential inputs for the neural network. The actual inputs and number of neurons to be employed are selected by means of a multi-objective genetic algorithm.por
dc.identifier.citationFerreira, P.M.; Martins, I.; Ruano, A. E. Cloud and clear sky pixel classification in ground-based all-sky hemispherical digital images, Trabalho apresentado em Control Methodologies and Technology for Energy Efficiency, In Proceedings of the IFAC Conference on Control Methodologies and Technology for Energy Efficiency (2010), Vilamoura, 2010.por
dc.identifier.isbn9783902661685
dc.identifier.otherAUT: ARU00698;
dc.identifier.urihttp://hdl.handle.net/10400.1/2137
dc.language.isoengpor
dc.peerreviewedyespor
dc.publisherElsevier, IFACpor
dc.subjectImage thresholdingpor
dc.subjectSegmentationpor
dc.subjectCloudinesspor
dc.subjectNeural Networkspor
dc.titleCloud and clear sky pixel classification in ground-based all-sky hemispherical digital imagespor
dc.typeconference object
dspace.entity.typePublication
oaire.citation.conferencePlaceVilamourapor
oaire.citation.endPage6por
oaire.citation.startPage1por
oaire.citation.titleIFAC Conference on Control Methodologies and Technology for Energy Efficiency (2010)por
person.familyNameRuano
person.givenNameAntonio
person.identifier.orcid0000-0002-6308-8666
person.identifier.ridB-4135-2008
person.identifier.scopus-author-id7004284159
rcaap.rightsrestrictedAccesspor
rcaap.typeconferenceObjectpor
relation.isAuthorOfPublication13813664-b68b-40aa-97a9-91481a31ebf2
relation.isAuthorOfPublication.latestForDiscovery13813664-b68b-40aa-97a9-91481a31ebf2

Files

Original bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
ifac-cmtee-2010001-01mar-0273ferr.pdf
Size:
570.4 KB
Format:
Adobe Portable Document Format
License bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
1.71 KB
Format:
Item-specific license agreed upon to submission
Description: