杨艳, 滕光辉, 李保明, 施正香. 基于计算机视觉技术估算种猪体重的应用研究[J]. 农业工程学报, 2006, 22(2): 127-131.
    引用本文: 杨艳, 滕光辉, 李保明, 施正香. 基于计算机视觉技术估算种猪体重的应用研究[J]. 农业工程学报, 2006, 22(2): 127-131.
    Yang Yan, Teng Guanghui, Li Baoming, Shi Zhengxiang. Measurement of pig weight based on computer vision[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2006, 22(2): 127-131.
    Citation: Yang Yan, Teng Guanghui, Li Baoming, Shi Zhengxiang. Measurement of pig weight based on computer vision[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2006, 22(2): 127-131.

    基于计算机视觉技术估算种猪体重的应用研究

    Measurement of pig weight based on computer vision

    • 摘要: 为了解决在种猪体重测量中传统方法所遇见的问题,该研究初步探讨了一种新方法,即把计算机视觉技术应用到种猪饲养管理中,通过数字图像分析技术,测量和计算种猪的投影面积,并分析其与体重的相关性,为种猪体重测量提供了新的依据。结果显示去除头部和尾部后剩余身体部分的投影面积和体重的相关性极大,相关系数可达到0.94,再与人工测量的结果进行对比,相对误差不超过2.8%。试验证实了利用这种无接触的方法来估测种猪的体重,可以减少人力物力,避免由于猪的应激反应而给生产带来的损失,在种猪的科学饲养管理中具有实用意义。

       

      Abstract: By analyzing the problems of traditional methods for estimating the weight of pigs, the authors discuss a new method which applies computer vision technology to pig production. The projected image area of pigs when viewed directly from above was computed. The pig weights were estimated by the linear regression of the pig real areas. The results show that a strong relationship exists between pig weight and the projected area of the pig after removing the sections of head and tail in images. The correlation coefficient is 0.94. By comparing with the measured weights, the relative error is less than 2.8%. The experiment indicates that this hands-off method has great significance in scientific management of the pigs, which does not require large labor and material resources, and also avoid the loss in production resulted from stress.

       

    /

    返回文章
    返回