Publication: Analysing muzzle pattern images as a biometric for cattle identification
Issued Date
2021-01-01
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video/youtube
ISSN
1755831X
17558301
17558301
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2-s2.0-85116713014
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Mahidol University
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SCOPUS
Bibliographic Citation
International Journal of Biometrics. Vol.13, No.4 (2021), 367-384
Suggested Citation
Worapan Kusakunniran, Anuwat Wiratsudakul, Udom Chuachan, Thanandon Imaromkul, Sarattha Kanchanapreechakorn, Noppanut Suksriupatham, Kittikhun Thongkanchorn Analysing muzzle pattern images as a biometric for cattle identification. International Journal of Biometrics. Vol.13, No.4 (2021), 367-384. doi:10.1504/IJBM.2021.117852 Retrieved from: https://repository.li.mahidol.ac.th/handle/20.500.14594/76733
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Title
Analysing muzzle pattern images as a biometric for cattle identification
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Abstract
Identifying individual animals is important for many reasons of population control, illegal trade prevention, and disease surveillance. This paper focuses on the cattle identification, using biometric-based solution of muzzle images. The proposed method begins with localising muzzle region in each image using the Haar-cascade-based classifier. The scale-invariant feature transform (SIFT) is applied to extract key points of muzzle patterns. Then, SIFT points are split into different clusters/types of muzzle patterns, called bags of muzzle-words (BoM). Finally, the support vector machine (SVM) model is built on BoM as the cattle identifier. The proposed method is evaluated on the published muzzle images dataset of cattle and the collected muzzle image dataset of slaughterhouses and preserved muzzles of swamp buffalo. This article reports the perfect accuracy of 100%. It is also evaluated with the collected dataset of muzzle images of swamp buffalo in the real fields with the reported accuracy of above 90%.