农业机械学报2023，Vol.54Issue(z1)：260-266,7.DOI:10.6041/j.issn.1000-1298.2023.S1.028
基于脸部RGB-D图像的牛只个体识别方法
Individual Identification of Cattle Based on RGB-D Images
摘要
Abstract
Individual identification is the foundation for achieving digital management of cattle.In order to achieve non-contact and high-precision individual identification,a dairy cow face recognition method based on RGB-D information fusion was proposed.Totally 108 Holstein cows aged 28 months to 30 months were selected as the research subjects,and 2 334 color/depth images of cattle faces were collected by using the Intel RealSense D455 depth camera as the original dataset.Firstly,image preprocessing was carried out by using redundant image elimination and adaptive threshold background separation algorithms.After enhancement,a total of 8 344 cattle face images was obtained as the dataset.Then,three feature extraction networks,including Inception ResNet v1,Inception ResNet v2,and SqueezeNet,were selected to extract the facial features of the cattle face.The optimal backbone feature extraction network of the FaceNet model was determined through comparative analysis.Finally,the extracted dairy cow face image features were L2 regularization and mapped to the same feature space.A classifier was trained to achieve individual classification of dairy cows.The test results showed that using Inception ResNet v2 as the backbone feature extraction network of the FaceNet model had the best performance.After testing the cow face recognition accuracy on the preprocessed dataset with background separation,the accuracy reached 98.6％,the verification rate was 81.9％,and the misidentification rate was 0.10％.Compared with that of Inception ResNet v1 and SqueezeNet networks,the accuracy was improved by 1 percentage points and 2.9 percentage points,respectively.Compared with that of the dataset without background separation,the accuracy was improved by 2.3 percentage points.The research result can provide a method for dairy cow face recognition.关键词
牛脸识别/RGB-D/深度学习/卷积神经网络Key words
cow face recognition/RGB-D/deep learning/convolutional neural network分类
信息技术与安全科学引用本文复制引用
刘世锋,常蕊,李斌,卫勇,王海峰,贾楠..基于脸部RGB-D图像的牛只个体识别方法[J].农业机械学报,2023,54(z1):260-266,7.基金项目
国家重点研发计划项目(2022YFD1301103)、国家农业智能装备工程技术研究中心实验室建设项目(PT2023-41)、北京市农林科学院创新能力建设专项(KJCX20230425)、北京市农林科学院改革与发展项目和北京市农林科学院开放项目(KFZN2020W011) （2022YFD1301103）
