Prediction of feather damage in laying hens using optical flows and Markov models
Prediction of feather damage in laying hens using optical flows and Markov models
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DOI：
10.1098/rsif.2010.0268
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发表时间：
2011-04-01
影响因子：
3.9
通讯作者：
Dawkins, Marian Stamp
中科院分区：
文献类型：
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作者：
Lee, Hyoung-Joo;Roberts, Stephen J.;Dawkins, Marian Stamp
对商业鸡蛋生产商来说，蛋鸡啄羽毛是一个主要的福利和生产问题，导致死亡、生产损失以及受损鸟类的福利问题。尽管提出了许多干预措施，但破坏性的啄羽毛爆发目前是无法控制的。然而，提前预测羽毛损伤的能力将是一个有价值的研究工具，用于确定哪些管理或环境因素可能是不同年龄最有效的干预措施。提出了一种基于自动图像处理和统计分析的损伤预测框架。通过对蛋鸡群录像的逐帧分析，计算出光流测度作为蛋鸡运动的指标。从光流数据集中，利用隐马尔可夫模型提取扰动测度。基于这些干扰测量和年龄相关变量，预测了未来几周鸡群的羽毛损伤水平。将提出的方法应用于现实世界的数据集，结果表明，干扰测量提供了更好的羽毛损伤预测值，从而能够识别出在产蛋期后期可能出现损伤和损伤的禽群。
Feather pecking in laying hens is a major welfare and production problem for commercial egg producers, resulting in mortality, loss of production as well as welfare issues for the damaged birds. Damaging outbreaks of feather pecking are currently impossible to control, despite a number of proposed interventions. However, the ability to predict feather damage in advance would be a valuable research tool for identifying which management or environmental factors could be the most effective interventions at different ages. This paper proposes a framework for forecasting the damage caused by injurious pecking based on automated image processing and statistical analysis. By frame-by-frame analysis of video recordings of laying hen flocks, optical flow measures are calculated as indicators of the movement of the birds. From the optical flow datasets, measures of disturbance are extracted using hidden Markov models. Based on these disturbance measures and age-related variables, the levels of feather damage in flocks in future weeks is predicted. Applying the proposed method to real-world datasets, it is shown that the disturbance measures offer improved predictive values for feather damage thus enabling an identification of flocks with probable prevalence of damage and injury later in lay.