Author(s)

Shengkun Yu ¹, Dongxin Wang ¹, Hongbing Huo ¹, Yining Liu ¹, Kaidi Fu ¹, Xinru Mu ¹, Binkai Zou ¹

Affiliation(s)

¹ School of Information and Electrical Engineering, Heilongjiang Bayi Agricultural University, Daqin 163000, China

Corresponding Author

Dongxin Wang

ABSTRACT

In the process of modern large-scale pig breeding, it is necessary to distinguish the identity of each pig and real-time detect its health status, weight change, dietary status, and other parameters. Traditional methods waste a lot of resources, while the high quality of pork cannot be effectively guaranteed. This project is based on convolutional neural networks to design and develop a pig face recognition system. This system uses an overhead camera suspended above the pig house to monitor the pig house for 24 hours and identify and track each pig. Due to the rapid growth cycle of the pig, the facial image information changes rapidly, which has a significant impact on the pig face recognition model. The acquisition camera module is designed to correct monitoring and tracking data. The acquisition camera is installed in the necessary place of the pig every day to collect real-time information and upload the collected information to the server. By comparing the data of individual pigs at different developmental stages with the server, the identification information of individual pigs is determined, and tracking data is corrected in a timely manner. At the same time, the monitoring and identification screen is displayed on the screen, and behavioral information parameters are recorded to facilitate the information management and breeding of the farm.

KEYWORDS

Pig face recognition, Information farming, AI, OpenCV, YOLO

CITE THIS PAPER

Shengkun Yu, Dongxin Wang, Hongbing Huo, Yining Liu, Kaidi Fu, Xinru Mu, Binkai Zou, A Method for Eliminating Pig Face Recognition Errors Caused by Too Short Pig Growth Cycle. Journal of Artificial Intelligence Practice (2023) Vol. 6: 57-62. DOI: http://dx.doi.org/10.23977/jaip.2023.060307.

REFERENCES

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[3] Miao Zheng. Research on pig face recognition algorithm based on deep learning. Shandong University of Commerce and Industry, 2022. DOI: 10.279 03/d.cnki.gsdsg.2022.000124
[4] Qin Xing, Song Fangfang. Pig face recognition algorithm based on bilinear convolutional neural network. Journal of Hangzhou University of Electronic Science and Technology: Natural Science Edition, 2019 (2): 12-17
[5] Luo Yibin, Hong Yuanquan, Zhou Yonglun, Cheng Xuelei, Guo Zhuohao. OpenCV based face mask specification wear detection. Electronic Technology and Software Engineering, 2023 (01): 153-158
[6] Ning Jifeng, Lin Jingya, Yang Shuqin, Wang Yongsheng, Lan Xianyong. A face recognition method for dairy goats based on improved YOLO v5s. Journal of Agricultural Machinery: 1-12 [2023-03-28] http://kns.cnki.net/kcms/detai L/11.1964.S.20230306.1228.002.html
[7] Zhang Jianlong, Zhou Kang, Zhuang Yanrong, Teng Guanghui. The effect of facial changes on the accuracy of recognition models during the growth of finishing pigs. Journal of China Agricultural University, 2021, 26 (06): 180-186.

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