Cattle Identification using Muzzle Images
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F16%3A86096029" target="_blank" >RIV/61989100:27240/16:86096029 - isvavai.cz</a>
Result on the web
<a href="http://link.springer.com/chapter/10.1007/978-3-319-29504-6_11" target="_blank" >http://link.springer.com/chapter/10.1007/978-3-319-29504-6_11</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-319-29504-6_11" target="_blank" >10.1007/978-3-319-29504-6_11</a>
Alternative languages
Result language
angličtina
Original language name
Cattle Identification using Muzzle Images
Original language description
The quality of animal identification system plays an important role for producers to make management decisions about their herd or individual animals. The animal identification is also important to animal traceability systems to ensure the integrity of the food chain. Usually, recordings and readings of tags-based systems are used to identify an animal, but only effective in eradication programs of national disease. Recently, animal biometric-based solutions, e.g. muzzle imaging system, offer an effective and secure, and rapid method of addressing the requirements of animal identification and traceability systems. In this paper, we present an identification system based on muzzle images. The identification process is based on Support Vector Machine (SVM), Linear Discriminant Analysis (LDA) and Tucker Tensor Decomposition. This selected classifiers we compared on the same dataset of muzzle images with different experiment settings. The results we evaluated by F-score. The best F-score result gives us the Tucker Tensor Decomposition. It achieved the median of F-score 0.750.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
IN - Informatics
OECD FORD branch
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Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2016
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Advances in Intelligent Systems and Computing. Volume 427
ISBN
978-3-319-29503-9
ISSN
2194-5357
e-ISSN
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Number of pages
10
Pages from-to
105-115
Publisher name
Springer Verlag
Place of publication
London
Event location
Paříž
Event date
Sep 9, 2015
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000371912400011