Worapan KusakunniranAnuwat WiratsudakulUdom ChuachanThanandon ImaromkulSarattha KanchanapreechakornNoppanut SuksriupathamKittikhun ThongkanchornMahidol UniversityVeterinary Research and Development Center2022-08-042022-08-042021-01-01International Journal of Biometrics. Vol.13, No.4 (2021), 367-3841755831X175583012-s2.0-85116713014https://repository.li.mahidol.ac.th/handle/20.500.14594/76733Identifying 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%.video/youtubeMahidol UniversityComputer ScienceEngineeringMathematicsArticleSCOPUS10.1504/IJBM.2021.117852