基于机器视觉技术的猪行为活动无接触识别系统
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贵州省科技厅重大专项(黔科合重大专项字[2016]3001号)


Contactless Identification System for Pig Behavior Based on Machine Vision
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    摘要:

    信息化和智能化是今后猪养殖产业的主要发展模式,为实现智能化识别猪的行为活动,从而监测猪的健康和生长情况,提出了一种基于机器视觉技术的无接触识别猪行为活动系统.该系统通过CCD相机采集猪行为活动序列图像,利用卷积神经网络提取图像深度特征,再使用特征融合方法融合图像深度特征,最后根据融合的深度特征识别序列图像中猪的行为活动.该系统能高精度识别自然场景下拍摄的猪的运动行为、跛足行为、伏地行为、呼吸行为、饮食行为和排泄行为等活动,对各类行为的识别准确率均在94%以上,均高于现有方法或与现有方法识别准确率相当.

    Abstract:

    In the future, the main development mode of pig breeding industry is information and intelligence. In order to monitor the behavior of pigs intelligently, so as to monitor the health and growth of pigs, this paper presents a system technology for contactless identification and monitoring pig behavior based on machine vision. The system collects pig behavior sequence images by CCD camera, then extracts the depth features of those images using convolution neural network. After that, the feature fusion method is used to fuse the depth features of the behavior sequence images. Finally, the pig’s behavior activities are identified according to the fusion depth feature. The system realizes the high-precision identification of pig’s motion behavior, claudication behavior, volt behavior, breathing behavior, eating behavior, and excretion behavior under natural scenes. The accuracy rates of recognizing all kinds of behavior are more than 94%, which are higher than the state-of-the-art methods.

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吴世海,鲍义东,陈果,陈秋实.基于机器视觉技术的猪行为活动无接触识别系统.计算机系统应用,2020,29(4):113-117

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  • 收稿日期:2019-09-02
  • 最后修改日期:2019-09-23
  • 在线发布日期: 2020-04-09
  • 出版日期: 2020-04-15
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