Cattle Identification using Muzzle Images

Kód výsledku v 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>

Výsledek na webu

<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>

Jazyk výsledku

angličtina

Název v původním jazyce

Cattle Identification using Muzzle Images

Popis výsledku v původním jazyce

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.

Název v anglickém jazyce

Cattle Identification using Muzzle Images

Popis výsledku anglicky

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.

Druh

D - Stať ve sborníku

CEP obor

IN - Informatika

OECD FORD obor

—

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2016

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Advances in Intelligent Systems and Computing. Volume 427

ISBN

978-3-319-29503-9

ISSN

2194-5357

e-ISSN

—

Počet stran výsledku

10

Strana od-do

105-115

Název nakladatele

Springer Verlag

Místo vydání

London

Místo konání akce

Paříž

Datum konání akce

9. 9. 2015

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000371912400011