Vision-based measuring method for individual cow feed intake using depth images and a Siamese network

IF 2.2 2区农林科学 Q2 AGRICULTURAL ENGINEERING

International Journal of Agricultural and Biological Engineering Pub Date : 2023-01-01 DOI:10.25165/j.ijabe.20231603.7985

Xinjie Wang, Baisheng Dai, Xiaoli Wei, Weizheng Shen, Yonggen Zhang, Benhai Xiong

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引用次数: 0

Abstract

Feed intake is an important indicator to reflect the production performance and disease risk of dairy cows, which can also evaluate the utilization rate of pasture feed. To achieve an automatic and non-contact measurement of feed intake, this paper proposes a method for measuring the feed intake of cows based on computer vision technology with a Siamese network and depth images. An automated data acquisition system was first designed to collect depth images of feed piles and constructed a dataset with 24 150 samples. A deep learning model based on the Siamese network was then constructed to implement non-contact measurement of feed intake for dairy cows by training with collected data. The experimental results show that the mean absolute error (MAE) and the root mean square error (RMSE) of this method are 0.100 kg and 0.128 kg in the range of 0-8.2 kg respectively, which outperformed existing works. This work provides a new idea and technology for the intelligent measuring of dairy cow feed intake. Keywords: computer vision, Siamese network, cow feed intake, depth image, precision livestock farming DOI: 10.25165/j.ijabe.20231603.7985 Citation: Wang X J, Dai B S, Wei X L, Shen W Z, Zhang Y G, Xiong B H. Vision-based measuring method for individual cow feed intake using depth images and a Siamese network. Int J Agric & Biol Eng, 2023; 16(3): 233–239.

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基于深度图像和暹罗网络的奶牛采食量视觉测量方法

采食量是反映奶牛生产性能和疾病风险的重要指标，也是评价牧草饲料利用率的重要指标。为了实现采食量的自动非接触测量，本文提出了一种基于暹罗网络和深度图像的计算机视觉技术测量奶牛采食量的方法。首先设计了自动数据采集系统，采集饲料桩深度图像，构建了24 150个样本的数据集。然后构建基于Siamese网络的深度学习模型，通过对收集到的数据进行训练，实现奶牛采食量的非接触测量。实验结果表明，该方法在0 ~ 8.2 kg范围内的平均绝对误差(MAE)为0.100 kg，均方根误差(RMSE)为0.128 kg，优于现有方法。为奶牛采食量的智能测量提供了新的思路和技术。关键词:计算机视觉，Siamese网络，奶牛采食量，深度图像，畜牧精准养殖DOI: 10.25165/ j.j ijabe.20231603.7985引用本文:王小杰，戴宝生，魏小林，沈文忠，张永刚，熊宝华。基于深度图像和Siamese网络的奶牛个体采食量视觉测量方法。农业与生物工程学报，2023;16(3): 233 - 239。

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来源期刊

International Journal of Agricultural and Biological Engineering AGRICULTURAL ENGINEERING-

CiteScore

4.30

自引率

12.50%

发文量

审稿时长

24 weeks

期刊介绍： International Journal of Agricultural and Biological Engineering (IJABE, https://www.ijabe.org) is a peer reviewed open access international journal. IJABE, started in 2008, is a joint publication co-sponsored by US-based Association of Agricultural, Biological and Food Engineers (AOCABFE) and China-based Chinese Society of Agricultural Engineering (CSAE). The ISSN 1934-6344 and eISSN 1934-6352 numbers for both print and online IJABE have been registered in US. Now, Int. J. Agric. & Biol. Eng (IJABE) is published in both online and print version by Chinese Academy of Agricultural Engineering.