research-article

Estimation of pig weight using a Microsoft Kinect prototype imaging system

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Jørgen KongsroAuthors Info & Claims

Computers and Electronics in Agriculture, Volume 109, Issue C

Pages 32 - 35

https://doi.org/10.1016/j.compag.2014.08.008

Published: 01 November 2014 Publication History

Abstract

Display Omitted A Kinect prototype for estimation the weight of pigs is presented.The depth map images from Kinect adds information about animal height in addition to area.Manual intervention with respect to image quality is needed in prototype method.The accuracy of the Kinect prototype is 4-5% of mean weight. The weight or mass of a pig is of great importance for farmers and stockmen to monitor performance, health and market weight of animals. The paper presents a prototype for pig weighing based on the Microsoft Kinect camera technology, utilizing the infrared depth map images. The system successfully estimated the weight of two different purebred breeds, landrace and duroc with an error estimate of 4-5% of mean weight. The depth map images require less calibration, are less prone to background (i.e. floor) noise compared to visible light camera systems and seem to be more robust between breeds due to additional information from height (depth map) of animals.

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Zhao YXiao QLi JTian KYang LShan PLv XLi LZhan Z(2024)Review on image-based animals weight weighingComputers and Electronics in Agriculture10.1016/j.compag.2023.108456215:COnline publication date: 27-Feb-2024
https://dl.acm.org/doi/10.1016/j.compag.2023.108456
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cover image Computers and Electronics in Agriculture

Computers and Electronics in Agriculture Volume 109, Issue C

November 2014

312 pages

ISSN:0168-1699

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Elsevier Science Publishers B. V.

Netherlands

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Published: 01 November 2014

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Zhao YXiao QLi JTian KYang LShan PLv XLi LZhan Z(2024)Review on image-based animals weight weighingComputers and Electronics in Agriculture10.1016/j.compag.2023.108456215:COnline publication date: 27-Feb-2024
https://dl.acm.org/doi/10.1016/j.compag.2023.108456
He CQiao YMao RLi MWang M(2023)Enhanced LiteHRNet based sheep weight estimation using RGB-D imagesComputers and Electronics in Agriculture10.1016/j.compag.2023.107667206:COnline publication date: 1-Mar-2023
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