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基于機器視覺的母豬分娩檢測方法研究
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公益性行業(yè)（農(nóng)業(yè)）科研專項經(jīng)費資助項目（201003011）和南京農(nóng)業(yè)大學(xué)青年科技基金資助項目（KJ2011021）


Sows Parturition Detection Method Based on Machine Vision
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    摘要:

    檢測母豬分娩需對分娩限位欄內(nèi)的仔豬進(jìn)行目標(biāo)識別，分析了母豬分娩視頻圖像特征，提出首先利用半圓匹配算法進(jìn)行母豬目標(biāo)分割，排除母豬運動干擾，基于改進(jìn)的單高斯模型的背景減除法進(jìn)行運動目標(biāo)檢測，根據(jù)運動區(qū)域的顏色和面積特征，對仔豬進(jìn)行目標(biāo)識別。試驗表明：基于半圓匹配算法的母豬目標(biāo)識別方法能夠有效分割出母豬目標(biāo)，基于改進(jìn)單高斯模型的運動目標(biāo)檢測方法，對面積較大、運動緩慢的仔豬目標(biāo)檢測較為完整，適用于母豬分娩檢測場景。

    Abstract:

    Automation and industrialization is the trend of pig industry. Real time detection of parturition is one of the key technologies of sow automation farming. Video image features of sows parturition were analyzed to detect sows parturition by recognizing piglet. The moving objects were detected based on the improved single Gaussian model. Disturbance of sow moving was removed by the arithmetic of matching semi circle. According to the color and size characteristics of newborn piglets, targets were recognized. Test results showed that the sow object could be recognized effectively by the proposed approach. The moving objects detection method based on the improved single Gaussian model detected the slow moving piglet completely after eliminate interference.

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劉龍申,沈明霞,柏廣宇,周 波,陸明洲,楊曉靜.基于機器視覺的母豬分娩檢測方法研究[J].農(nóng)業(yè)機械學(xué)報,2014,45(3):237-242. Liu Longshen, Shen Mingxia, Bo Guangyu, Zhou Bo, Lu Mingzhou, Yang Xiaojing. Sows Parturition Detection Method Based on Machine Vision[J]. Transactions of the Chinese Society for Agricultural Machinery,2014,45(3):237-242.

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  • 收稿日期:2013-03-14
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  • 在線發(fā)布日期: 2014-03-10
  • 出版日期: 2014-02-10