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1. Identity statement
Reference TypeConference Paper (Conference Proceedings)
Sitesibgrapi.sid.inpe.br
Holder Codeibi 8JMKD3MGPEW34M/46T9EHH
Identifier8JMKD3MGPEW34M/45CALPL
Repositorysid.inpe.br/sibgrapi/2021/09.02.18.48
Last Update2021:09.02.18.48.48 (UTC) administrator
Metadata Repositorysid.inpe.br/sibgrapi/2021/09.02.18.48.48
Metadata Last Update2022:06.14.00.00.21 (UTC) administrator
DOI10.1109/SIBGRAPI54419.2021.00047
Citation KeyBehaineIde:2021:EgImNo
TitleAn egg image noise model for digital visual counting processing
FormatOn-line
Year2021
Access Date2024, May 07
Number of Files1
Size1106 KiB
2. Context
Author1 Behaine, Carlos Alberto Ramirez
2 Ide, Jaime S
Affiliation1 University of Passo Fundo, Brazil 
2 Yale University, USA
EditorPaiva, Afonso
Menotti, David
Baranoski, Gladimir V. G.
Proença, Hugo Pedro
Junior, Antonio Lopes Apolinario
Papa, João Paulo
Pagliosa, Paulo
dos Santos, Thiago Oliveira
e Sá, Asla Medeiros
da Silveira, Thiago Lopes Trugillo
Brazil, Emilio Vital
Ponti, Moacir A.
Fernandes, Leandro A. F.
Avila, Sandra
e-Mail Addresscramireb@hotmail.com
Conference NameConference on Graphics, Patterns and Images, 34 (SIBGRAPI)
Conference LocationGramado, RS, Brazil (virtual)
Date18-22 Oct. 2021
PublisherIEEE Computer Society
Publisher CityLos Alamitos
Book TitleProceedings
Tertiary TypeFull Paper
History (UTC)2021-09-02 18:48:48 :: cramireb@hotmail.com -> administrator ::
2022-03-02 00:54:15 :: administrator -> menottid@gmail.com :: 2021
2022-03-02 13:20:45 :: menottid@gmail.com -> administrator :: 2021
2022-06-14 00:00:21 :: administrator -> :: 2021
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Version Typefinaldraft
Keywordsimage noise models
visual counting processing
AbstractContactless counting is a suitable technique for the measurement of fragile commodities, acting as a successful tool for industrial production control. Visual counting processing is one of the most common contactless methods for non-invasive measurements. However, the creation of accurate models for processing images in realistic scenarios is still challenging due to the existence of noise in optical sensors. This paper proposes an egg image noise model for digital visual counting processing that incorporates particular aspects of real images in such acquisition systems. The matching function is defined in hue saturation value (HSV) color space, and a classical nearest neighbor cluster classification is utilized for the counting. Validation experiments are executed with low and high diversity test images, and the performance of the proposed model is compared to existing methods. The matching function results suggest that the introduced egg image noise model is able to represent more accurately complex aspects of egg images in an industrial environment. The comparative results show that the proposed model significantly improves digital visual counting, in terms of egg counting errors, and outperforms in 9% the second best method.
Arrangement 1urlib.net > SDLA > Fonds > SIBGRAPI 2021 > An egg image...
Arrangement 2urlib.net > SDLA > Fonds > Full Index > An egg image...
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4. Conditions of access and use
data URLhttp://urlib.net/ibi/8JMKD3MGPEW34M/45CALPL
zipped data URLhttp://urlib.net/zip/8JMKD3MGPEW34M/45CALPL
Languageen
Target FilePaper ID 8.pdf
User Groupcramireb@hotmail.com
Visibilityshown
Update Permissionnot transferred
5. Allied materials
Mirror Repositorysid.inpe.br/banon/2001/03.30.15.38.24
Next Higher Units8JMKD3MGPEW34M/45PQ3RS
8JMKD3MGPEW34M/4742MCS
Citing Item Listsid.inpe.br/sibgrapi/2021/11.12.11.46 5
Host Collectionsid.inpe.br/banon/2001/03.30.15.38
6. Notes
Empty Fieldsarchivingpolicy archivist area callnumber contenttype copyholder copyright creatorhistory descriptionlevel dissemination edition electronicmailaddress group isbn issn label lineage mark nextedition notes numberofvolumes orcid organization pages parameterlist parentrepositories previousedition previouslowerunit progress project readergroup readpermission resumeid rightsholder schedulinginformation secondarydate secondarykey secondarymark secondarytype serieseditor session shorttitle sponsor subject tertiarymark type url volume


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