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dc.contributor.authorHao, Yan
dc.contributor.authorYi, Zhang
dc.contributor.authorZeng-guang, Hou
dc.contributor.authorMin, Tan
dc.contributor.editorSkala, Václav
dc.date.accessioned2013-04-16T09:37:50Z-
dc.date.available2013-04-16T09:37:50Z-
dc.date.issued2003
dc.identifier.citationJournal of WSCG. 2003, vol. 11, no. 1-3.en
dc.identifier.issn1213-6972
dc.identifier.urihttp://wscg.zcu.cz/wscg2003/Papers_2003/D31.pdf
dc.identifier.urihttp://hdl.handle.net/11025/1666
dc.description.abstractIn this paper, one novel approach for text detection in video frames, which is based on bootstrap artificial neural network (BANN) and CED operator, is proposed. This method first uses a new color image edge operator (CED) to segment the image and achieve the elementary candidate text block. And then the neural network is introduced into the further classification of the text blocks and the non-text blocks in video frames. The idea of bootstrap is introduced into the training of the ANN, thus improving the effectiveness of the neural network greatly. Experiments results proved that this method is effective.en
dc.format6 s.cs
dc.format.mimetypeapplication/pdf
dc.language.isoenen
dc.publisherUNION Agency – Science Presscs
dc.relation.ispartofseriesJournal of WSCGen
dc.rights© UNION Agency – Science Presscs
dc.subjectdetekce textucs
dc.subjectumělá neuronová síťcs
dc.subjectvideo snímkycs
dc.titleAutomatic text detection in video frames based on bootstrap artificial neural network and CEDen
dc.typečlánekcs
dc.typearticleen
dc.rights.accessopenAccessen
dc.type.versionpublishedVersionen
dc.subject.translatedtext detectionen
dc.subject.translatedartificial neural networken
dc.subject.translatedvideo framesen
dc.type.statusPeer-revieweden
Vyskytuje se v kolekcích:Volume 11, number 1-3 (2003)

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