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首页> 外文期刊>Computers and Electronics in Agriculture >Automatic detection of lameness in dairy cattle--Vision-based trackway analysis in cow's locomotion
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Automatic detection of lameness in dairy cattle--Vision-based trackway analysis in cow's locomotion

机译:奶牛la行症的自动检测-基于视觉的奶牛运动轨迹分析

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The occurrence of lameness in dairy cattle is of increasing importance in herd health management and herd productivity. Current practice, involves visual observation by human experts to score cow's locomotion in order to estimate the lameness in the herd. The trackway defined as hind hoof compared to fore hoof position is one of the main components to score the locomotion. However, because of the time-consuming observation method, lame cows are undiagnosed until the problem has become severe. Up till now there is no automatic (visual) method for detecting lameness in dairy cattle. The objective of our study was to make an automatic system for continuous on-farm detection and prediction of lameness in the farm by using vision techniques. The current focus was on demonstrating the possibility of capturing cow's hoof locations by vision and strong correlation between automatically calculated hoof trackway and visual locomotion scores. Fifteen selected lactating cows were scored visually by four trained observers at the Gent University Research Farm. Scoring varied from 1 (normal walking) to 5 (extremely lame). Side-view images with resolution of 1024x768pixels were recorded when cows passed an experimental set-up freely. Recorded videos were split into sequences of bitmap images. After background subtraction, binary image operations, calibration and hoof separation, the trackway information containing hoof location in the real world and its related time in the video was calculated. The accuracy of automatically captured results was checked by comparing with the output from manually labeled hoof locations. The mean correlation coefficient of all measurements was 94.8%. Hence, the results suggest that the automatic method by vision analysis is feasible to present the cows' real locomotion situations. The first result showed a positive linear relationship between cows' trackways overlap and locomotion scores by human visualization. This research proved that vision techniques have great potential to be used for continuous quantification of lameness in cows.
机译:奶牛la行的发生在畜群健康管理和畜群生产力中具有越来越重要的意义。当前的做法是由人类专家目视观察以对奶牛的运动进行评分,以估计牛群中的la行。与前蹄位置相比,被定义为后蹄的轨道是对运动进行评分的主要组成部分之一。但是,由于耗时的观察方法,直到问题变得严重之前,la牛才被诊断出来。到目前为止,还没有用于检测奶牛la行的自动(可视)方法。我们研究的目的是使用视觉技术制作一个自动系统,用于农场的连续农场检测和prediction行预测。当前的重点是展示通过视觉捕获牛的蹄位置的可能性以及自动计算的蹄轨迹和视觉运动得分之间的强相关性。根特大学研究农场的四名训练有素的观察员对15头选择的泌乳母牛进行了视觉评分。得分从1(正常步行)到5(极度la脚)不等。当母牛自由通过实验装置时,记录了分辨率为1024x768像素的侧视图图像。录制的视频被分成位图图像序列。经过背景扣除,二值图像操作,校准和蹄分离之后,计算出包含现实中蹄位置及其在视频中的相关时间的轨道信息。通过与手动标记的蹄位置的输出进行比较,检查了自动捕获结果的准确性。所有测量的平均相关系数为94.8%。因此,结果表明,通过视觉分析的自动方法可用于介绍奶牛的真实运动情况。第一个结果显示,通过人类可视化,奶牛的走道重叠与运动得分之间存在正线性关系。这项研究证明,视觉技术具有巨大的潜力,可用于连续量化奶牛的continuous行。

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