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1. Identity statement
Reference TypeConference Paper (Conference Proceedings)
Sitesibgrapi.sid.inpe.br
Holder Codeibi 8JMKD3MGPEW34M/46T9EHH
Identifier8JMKD3MGPEW34M/45E886B
Repositorysid.inpe.br/sibgrapi/2021/09.14.12.33
Last Update2021:10.05.19.52.34 (UTC) administrator
Metadata Repositorysid.inpe.br/sibgrapi/2021/09.14.12.33.11
Metadata Last Update2022:09.10.00.16.17 (UTC) administrator
Citation KeyWojcikMenoHill:2021:SeGrGe
TitleSegmentation and graph generation of muzzle images for cattle identification
FormatOn-line
Year2021
Access Date2024, Mar. 28
Number of Files1
Size935 KiB
2. Context
Author1 Wojcik, Lucas Matheus Leite
2 Jorge Junior
3 Menotti, David
4 Hill, João
Affiliation1 Federal University of Paraná (UFPR)
2 Federal University of Paraná (UFPR)
3 Federal University of Paraná (UFPR)
4 Institute of Rural Development of Paraná (IDR)
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 Addresslasse1999st@gmail.com
Conference NameConference on Graphics, Patterns and Images, 34 (SIBGRAPI)
Conference LocationGramado, RS, Brazil (virtual)
Date18-22 Oct. 2021
PublisherSociedade Brasileira de Computação
Publisher CityPorto Alegre
Book TitleProceedings
Tertiary TypeWork in Progress
History (UTC)2021-10-05 19:52:34 :: lasse1999st@gmail.com -> administrator :: 2021
2022-09-10 00:16:17 :: administrator -> :: 2021
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
KeywordsAnimal biometrics
Computer vision
Pattern recognition
AbstractThe current methods for the organizing the records (i.e., cataloguing) of cattle are known to be archaic and inefficient, and often harmful to the animal. Such methods include the use of metal tags attached to the animal's ears like earrings and of branding irons on their necks. Previous research on new methods of livestock branding based on computer vision techniques utilized a mixture of texture features such as Gabor Filters and Local Binary Pattern as a means of extracting identifying features for each animal. The presented approach proposes a new technique using the muzzle image as an individual identifier as a novel technique, assuming that the muzzle RoI taken as input for the model pipeline is already extracted and cropped. This task is performed in three steps. First, the muzzle image is segmented via a convolutional neural network, resulting in a bitmap from which a graph structure is extracted in the second phase. The final phase consists of matching the resulting graph with the ones previously extracted and stored in the database for an optimal match. The results for the segmentation quality show a fidelity of around seventy percent, while the extracted graph perfectly represents the extracted bitmap. The matching algorithm is currently in progress.
Arrangementurlib.net > SDLA > Fonds > SIBGRAPI 2021 > Segmentation and graph...
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4. Conditions of access and use
data URLhttp://urlib.net/ibi/8JMKD3MGPEW34M/45E886B
zipped data URLhttp://urlib.net/zip/8JMKD3MGPEW34M/45E886B
Languageen
Target File2021_WIP_IDR_SegmentMatch(4).pdf
User Grouplasse1999st@gmail.com
Visibilityshown
5. Allied materials
Mirror Repositorysid.inpe.br/banon/2001/03.30.15.38.24
Next Higher Units8JMKD3MGPEW34M/45PQ3RS
Host Collectionsid.inpe.br/banon/2001/03.30.15.38
6. Notes
Empty Fieldsarchivingpolicy archivist area callnumber contenttype copyholder copyright creatorhistory descriptionlevel dissemination documentstage doi 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 versiontype volume


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