Biometric cattle identification approach based on Weber’s Local Descriptor and AdaBoost classifier
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- 作者：Tarek Gabera ; b ; c ; tmgaber@gmail.com" class="auth_mail" title="E-mail the corresponding author ; Alaa Tharwatc ; d ; engalaatharwat@hotmail.com" class="auth_mail" title="E-mail the corresponding author ; Aboul Ella Hassanienc ; e ; aboitcairo@gmail.com" class="auth_mail" title="E-mail the corresponding author ; Vaclav Snaself ; Vaclav.Snasel@vsb.cz" class="auth_mail" title="E-mail the corresponding author
- 关键词：Cattle identification ; Weber Local Descriptor (WLD) ; k-Nearest Neighbor ; Fuzzy-k-Nearest Neighbor ; Muzzle print images ; AdaBoost classifier
- 刊名：Computers and Electronics in Agriculture
- 出版年：2016
- 出版时间：March 2016
- 年：2016
- 卷：122
- 期：Complete
- 页码：55-66
- 全文大小：1553 K
文摘
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Limitations and weakness of traditional cattle identification were highlighted.
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Cattle identification approach based on biometric features was proposed.
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Weber’s Local Descriptor (WLD) along with many classifiers were examined.
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Dataset of muzzle print images (images from 31 cattle animals) were used.
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The results were validated against False Accept and Reject rate, Sensitivity and Specificity, and accuracy.