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Pig Face Recognition Using Deep Learning

딥러닝을 이용한 돼지 얼굴 인식

  • MA, RUIHAN (Division of Electronics and Information Engineering, Jeonbuk National University) ;
  • Kim, Sang-Cheol (Intellignet Robots Research Center, Jeonbuk National University)
  • 마리한 (전북대학교 전자정보공학부) ;
  • 김상철 (전북대학교 지능형로봇연구소)
  • Published : 2022.11.21

Abstract

The development of livestock faces intensive farming results in a rising need for recognition of individual animals such as cows and pigs is related to high traceability. In this paper, we present a non-invasive biometrics systematic approach based on the deep-learning classification model to pig face identification. Firstly, in our systematic method, we build a ROS data collection system block to collect 10 pig face data images. Secondly, we proposed a preprocessing block in that we utilize the SSIM method to filter some images of collected images that have high similarity. Thirdly, we employ the improved image classification model of CNN (ViT), which uses the finetuning and pretraining technique to recognize the individual pig face. Finally, our proposed method achieves the accuracy about 98.66%.

Keywords

Acknowledgement

This research was supported by the Ministry of Agriculture, Food and Rural Affairs, the Ministry of Science and ICT, and the Rural Development Administration with the support of the Smart Farm Multi-Ministry Package Innovation Technology Development Project (421018-03, 421023-04)