Cattle identification using muzzle print images based on feature fusion

Abstract

Abstract Individual identification of animals is an important means to modernize the livestock industry. In recent years, the research on individual identification of cattle has also received more and more attention. Individual cattle identification is necessary for many important reasons including registration, traceability, production management and animal disease control. Biometric features are unique, which often do not change over time. In this paper, muzzle print is used as biometric feature. The fusion of texture features extracted from Weber Local Descriptor(WLD) and local binary pattern was used to represent individual cattle. Some improvements were made to WLD algorithm. Finally, support vector machine was employed to identify head of cattle from their fusion feature. The proposed method achieved 96.5% identification accuracy.