Application of machine vision to swine environmental control

Summary form only given. Use of computer vision to enhance animal well-being and overall production efficiency is expected to be characteristic of the future electronic stockmanship. This study explores the feasibility of the technique with growing pigs and identifies the areas that need further inv...

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Hauptverfasser: Hongwei Xin, Junqing Shao
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description Summary form only given. Use of computer vision to enhance animal well-being and overall production efficiency is expected to be characteristic of the future electronic stockmanship. This study explores the feasibility of the technique with growing pigs and identifies the areas that need further investigation. Specifically, nursery pigs were subjected, in groups of 10 pigs, to cold, comfortable, and warm environments. Postural behaviors of the pigs were captured at 40-minute intervals with programmable cameras overseeing the pig pen area. The raw behavioral images were processed by thresholding, edge detection, and morphological filtering to separate the pigs from their background. Feature extraction of Fourier coefficients, moments, perimeter and area, and combination of perimeter, area and moments was performed on the processed behavioral images. The selected features were used as the inputs to a 3-layer neural network which then classifies the pig behavior into cold, comfortable, or warm category.
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Use of computer vision to enhance animal well-being and overall production efficiency is expected to be characteristic of the future electronic stockmanship. This study explores the feasibility of the technique with growing pigs and identifies the areas that need further investigation. Specifically, nursery pigs were subjected, in groups of 10 pigs, to cold, comfortable, and warm environments. Postural behaviors of the pigs were captured at 40-minute intervals with programmable cameras overseeing the pig pen area. The raw behavioral images were processed by thresholding, edge detection, and morphological filtering to separate the pigs from their background. Feature extraction of Fourier coefficients, moments, perimeter and area, and combination of perimeter, area and moments was performed on the processed behavioral images. The selected features were used as the inputs to a 3-layer neural network which then classifies the pig behavior into cold, comfortable, or warm category.</description><subject>Animals</subject><subject>Application software</subject><subject>Cameras</subject><subject>Computer vision</subject><subject>Feature extraction</subject><subject>Filtering</subject><subject>Image edge detection</subject><subject>Machine vision</subject><subject>Neural networks</subject><subject>Production</subject><isbn>9780780340800</isbn><isbn>0780340809</isbn><fulltext>true</fulltext><rsrctype>book_chapter</rsrctype><creationdate>1997</creationdate><recordtype>book_chapter</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNotT01rwzAUM4zBRpfzYKf8gWTPL7FfDLuEso9Cxy69F9d53TwSO8ShY_9-KZ0QCOkgJCHuJZRSgnlsN--lNIZKrbAhvBKZoQYWVjU0ADciS-kbFtRKSaJb8dSOY--dnX0MeTzmg3VfPnB-8umczDFPP2fP4eSnGAYOs-1zF8M8xf5OXB9tnzj715XYvTzv1m_F9uN1s263xaeWWHADpmF0VrMGkqSc0x2oA6Izy0wEQLKV7nRtO3ZKG0TiuoYOqoMlpGolHi61npn34-QHO_3uLw-rP0B9RWE</recordid><startdate>1997</startdate><enddate>1997</enddate><creator>Hongwei Xin</creator><creator>Junqing Shao</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>1997</creationdate><title>Application of machine vision to swine environmental control</title><author>Hongwei Xin ; Junqing Shao</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-g612-e8098e2ca6e607175cc6d05b22c965220027a36d64adec569227e440d03ba7273</frbrgroupid><rsrctype>book_chapters</rsrctype><prefilter>book_chapters</prefilter><language>eng</language><creationdate>1997</creationdate><topic>Animals</topic><topic>Application software</topic><topic>Cameras</topic><topic>Computer vision</topic><topic>Feature extraction</topic><topic>Filtering</topic><topic>Image edge detection</topic><topic>Machine vision</topic><topic>Neural networks</topic><topic>Production</topic><toplevel>online_resources</toplevel><creatorcontrib>Hongwei Xin</creatorcontrib><creatorcontrib>Junqing Shao</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Electronic Library (IEL)</collection><collection>IEEE Proceedings Order Plans (POP All) 1998-Present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Hongwei Xin</au><au>Junqing Shao</au><format>book</format><genre>bookitem</genre><ristype>CHAP</ristype><atitle>Application of machine vision to swine environmental control</atitle><btitle>Proceedings of IEEE/ASME International Conference on Advanced Intelligent Mechatronics</btitle><stitle>AIM</stitle><date>1997</date><risdate>1997</risdate><spage>14</spage><pages>14-</pages><isbn>9780780340800</isbn><isbn>0780340809</isbn><abstract>Summary form only given. Use of computer vision to enhance animal well-being and overall production efficiency is expected to be characteristic of the future electronic stockmanship. This study explores the feasibility of the technique with growing pigs and identifies the areas that need further investigation. Specifically, nursery pigs were subjected, in groups of 10 pigs, to cold, comfortable, and warm environments. Postural behaviors of the pigs were captured at 40-minute intervals with programmable cameras overseeing the pig pen area. The raw behavioral images were processed by thresholding, edge detection, and morphological filtering to separate the pigs from their background. Feature extraction of Fourier coefficients, moments, perimeter and area, and combination of perimeter, area and moments was performed on the processed behavioral images. 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identifier ISBN: 9780780340800
ispartof Proceedings of IEEE/ASME International Conference on Advanced Intelligent Mechatronics, 1997, p.14
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language eng
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source IEEE Electronic Library (IEL) Conference Proceedings
subjects Animals
Application software
Cameras
Computer vision
Feature extraction
Filtering
Image edge detection
Machine vision
Neural networks
Production
title Application of machine vision to swine environmental control
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