Real-time recognition of cattle using animal biometrics

Abstract

With the advent of efficient recognition techniques, animal biometric systems have gained more proliferation for the identification and monitoring of cattle. A cattle biometric system is a pattern recognition-based system for the identification of livestock. In this paper, we propose a novel muzzle point recognition based on Fisher locality preserving projection algorithm for the recognition of cattle in real time. We have captured images of animals using a surveillance camera and transferred them to the server by wireless network technology. The major contributions are as follows: (1) preparation of muzzle point database, (2) extraction of the salient set of features using proposed muzzle point recognition approach, and (3) evaluation and comparison analysis of the introduced method and several existing recognition algorithms on a standard benchmark protocol. The efficacy of proposed muzzle point recognition approach for cattle evaluates under identification settings and yields \(96.87\,\%\) recognition accuracy for identifying individual cattle. The proposed approach also valued the 10.25 sec recognition time for enrollment and identified individual cattle on different sizes of muzzle point images.