Muzzle-based Cattle Identification using Speed up Robust Feature Approach

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F15%3A86099116" target="_blank" >RIV/61989100:27240/15:86099116 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/61989100:27740/15:86099116

Výsledek na webu

<a href="http://ieeexplore.ieee.org/document/7312056/" target="_blank" >http://ieeexplore.ieee.org/document/7312056/</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/INCoS.2015.60" target="_blank" >10.1109/INCoS.2015.60</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Muzzle-based Cattle Identification using Speed up Robust Feature Approach

Popis výsledku v původním jazyce

Starting from the last century, animals identification became important for several purposes, e.g. tracking, controlling livestock transaction, and illness control. Invasive and traditional ways used to achieve such animal identification in farms or laboratories. To avoid such invasiveness and to get more accurate identification results, biometric identification methods have appeared. This paper presents an invariant biometric-based identification system to identify cattle based on their muzzle print images. This system makes use of Speeded Up Robust Feature (SURF) features extraction technique along with with minimum distance and Support Vector Machine (SVM) classifiers. The proposed system targets to get best accuracy using minimum number of SURF interest points, which minimizes the time needed for the system to complete an accurate identification. It also compares between the accuracy gained from SURF features through different classifiers. The experiments run 217 muzzle print images and the experimental results showed that our proposed approach achieved an excellent identification rate compared with other previous works.

Název v anglickém jazyce

Muzzle-based Cattle Identification using Speed up Robust Feature Approach

Popis výsledku anglicky

Starting from the last century, animals identification became important for several purposes, e.g. tracking, controlling livestock transaction, and illness control. Invasive and traditional ways used to achieve such animal identification in farms or laboratories. To avoid such invasiveness and to get more accurate identification results, biometric identification methods have appeared. This paper presents an invariant biometric-based identification system to identify cattle based on their muzzle print images. This system makes use of Speeded Up Robust Feature (SURF) features extraction technique along with with minimum distance and Support Vector Machine (SVM) classifiers. The proposed system targets to get best accuracy using minimum number of SURF interest points, which minimizes the time needed for the system to complete an accurate identification. It also compares between the accuracy gained from SURF features through different classifiers. The experiments run 217 muzzle print images and the experimental results showed that our proposed approach achieved an excellent identification rate compared with other previous works.

Druh

D - Stať ve sborníku

CEP obor

IN - Informatika

OECD FORD obor

—

Projekt

Výsledek vznikl pri realizaci vícero projektů. Více informací v záložce Projekty.

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2015

Kód důvěrnosti údajů

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

Název statě ve sborníku

International Conference on Intelligent Networking and Collaborative Systems IEEE INCoS 2015 : Proceedings Papers

ISBN

978-1-4673-7695-2

ISSN

—

e-ISSN

—

Počet stran výsledku

6

Strana od-do

99-104

Název nakladatele

IEEE

Místo vydání

New York

Místo konání akce

Tchaj-pej

Datum konání akce

2. 9. 2015

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000380529500017