畜禽个体识别技术研究进展  

Review of Research Progress in Individual Identification Technology for Livestock and Poultry

作　　者：纪宝锋 周孟创 朱芷芫 陈嘉辉 朱君 李斌[1,2] JI Baofeng;ZHOU Mengchuang;ZHU Zhiyuan;CHEN Jiahui;ZHU Jun;LI Bin(Intelligent Equipment Research Center,Beijing Academy of Agriculture and Forestry Sciences,Beijing 100097,China;College of En gineering and Technology,Tianjin Agricultural University,Tianjin 300384,China)

机构地区：[1]北京市农林科学院智能装备技术研究中心,北京100097 [2]天津农学院工程技术学院,天津300384

出　　处：《中国猪业》2024年第3期47-58,共12页China Swine Industry

基　　金：国家重点研发计划(2022YFD1302101);北京市农林科学院科研创新平台(PT2024-41);北京市平谷区博士农场项目。

摘　　要：畜禽个体识别是实现精细化管理、智慧化养殖的重要前提。耳切、耳纹和热铁烙印等是传统人工辨别畜禽个体的方法,存在效率低、个体应激性大等问题,基于无线射频技术的个体识别方法应激程度小,但存在价格昂贵、易脱落、续航时间短等问题。近年来,随着机器视觉与深度学习技术的快速发展,非接触式个体识别方法成为当前研究热点之一。本文在充分梳理现有畜禽个体识别方法的基础上,介绍了典型的接触式个体识别方法及存在的优缺点,并分别阐述了基于图像处理和基于深度学习的2种非接触式畜禽个体识别方法及优缺点,总结分析了在畜禽个体识别中关于深度学习模型、样本数据量及研究层面等存在的问题和改进策略,提出了相关建议,可为养殖管理人员提供理论依据和技术支撑。Individual identification of livestock and poultry was an important prerequisite for achieving refined management and intelligent breeding.Traditional manual identification methods such as earprint ear patterning and hot iron branding faced issues of low identifica-tion efficiency and high individual stress.Individual identification based on radio frequency identification technology methods offers low stress levels but came with drawbacks such as high costs,prone to detachment and short battery life.With the rapid development of machine vision and deep learning technology,non-contact individual recognition methods had become one of the current research hotspots.On the basis of thoroughly reviewing the existing individual recognition methods,this paper introduced typical contact individ-ual recognition methods and their advantages and disadvantages,described two non-contact individual recognition methods based on image processing and deep learning and their advantages and disadvantages.Summarized and analyzed the problems and improve-ment strategies of deep learning in animal individual recognition,including deep learning models,sample data size and research level.Relevant suggestions were proposed,which could provide theoretical basis and technical support for breeding management personnel.

关 键 词：畜禽 机器视觉 深度学习 个体识别 

分 类 号：S818.9[农业科学—畜牧学] TP391.41[农业科学—畜牧兽医]