Open AccessCattle identification using muzzle print images based on feature fusion
Author(s) -
Sian Cong,
Jiye Wang,
Ru Zhang,
Lizhi Zhao
Publication year - 2020
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/853/1/012051
Subject(s) - muzzle , identification (biology) , traceability , biometrics , artificial intelligence , feature (linguistics) , computer science , pattern recognition (psychology) , local binary patterns , minutiae , computer vision , fingerprint (computing) , engineering , image (mathematics) , fingerprint recognition , biology , histogram , mechanical engineering , linguistics , philosophy , botany , software engineering , barrel (horology)
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.