康熙,张旭东,刘刚,马丽.基于机器视觉的跛行奶牛牛蹄定位方法[J].农业机械学报,2019,50(Supp):276-282.
KANG Xi,ZHANG Xudong,LIU Gang,MA Li.Hoof Location Method of Lame Dairy Cows Based on Machine Visio[J].Transactions of the Chinese Society for Agricultural Machinery,2019,50(Supp):276-282.
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基于机器视觉的跛行奶牛牛蹄定位方法   [下载全文]
Hoof Location Method of Lame Dairy Cows Based on Machine Visio   [Download Pdf][in English]
投稿时间:2019-04-15  
DOI:10.6041/j.issn.1000-1298.2019.S0.043
中文关键词:  奶牛  机器视觉  跛行  图像处理  时空变化
基金项目:国家重点研发计划项目(2018YFD0500705-2018YFD050070502)
作者单位
康熙 中国农业大学 
张旭东 中国农业大学 
刘刚 中国农业大学 
马丽 中国农业大学 
中文摘要:针对采用机器视觉技术检测奶牛跛行过程中不易准确、自动定位牛蹄位置的问题,提出一种奶牛牛蹄定位方法。通过对可见光视频中奶牛图像预处理,提取牛蹄二值化图像,研究奶牛行走时空特性,分析牛蹄在图像中的时空变化,提出一种时空差值算法,计算连通域最低点坐标,实现对奶牛牛蹄着地位置准确定位;通过分析奶牛行走时牛蹄的运动顺序,对同侧牛蹄位置数据进行提取分类,用于轨迹提取,检测跛行。进行了牛蹄定位试验和跛行检测试验,结果表明,牛蹄定位准确,阈值为20像素时精度达到73.8%,着地位置平均误差达到11.3像素;奶牛跛行检测准确率为93.3%,跛行分类准确率为77.8%。研究结果能较准确定位奶牛自然行走状况下牛蹄位置,可实现奶牛跛行的自动检测。
KANG Xi  ZHANG Xudong  LIU Gang  MA Li
China Agricultural University,China Agricultural University,China Agricultural University and China Agricultural University
Key Words:dairy cow  machine vision  lameness  image processing  temporal and spatial variation
Abstract:In order to solve the problem that it is not easy to accurately and automatically locate the hoof position of dairy cows in the process of lameness detection by machine vision technology, a method of hoof location for dairy cows was proposed. Through extraction of cow hoof image by preprocessing cow image in visible video, study on spatial temporal characteristics of dairy cows walking, analysis of temporal and spatial variations of cows hooves in images, a spatiotemporal difference algorithm was proposed, the lowest coordinates of connected domain was computed, and the cows’ hoofs were located accurately. Through analysis of the moving sequence of cows’ hoofs, extraction and classification of homologous hoof position data, the data requirement of the lameness track detection method was met to judge the lameness of dairy cows by using the hoof position of the same side of the cow before and after the lameness track detection method. The positioning test of cattle hoof and lameness test were carried out; this method can accurately locate the cows’ hoofs, when the threshold was 20 pixels the accuracy was 73.8%, the average error of calculating the landing position of cows’ hoofs reached 11.3 pixels, the accuracy of cow lameness track detection was 93.3%, the accuracy of lameness claudication was 77.8%, the results can accurately locate the hoofs of dairy cows under natural walking conditions, and realize automatic detection of lameness in dairy cows.

Transactions of the Chinese Society for Agriculture Machinery (CSAM), in charged of China Association for Science and Technology (CAST), sponsored by CSAM and Chinese Academy of Agricultural Mechanization Science(CAAMS), started publication in 1957. It is the earliest interdisciplinary journal in Chinese which combines agricultural and engineering. It always closely grasps the development direction of agriculture engineering disciplines and the published papers represent the highest academic level of agriculture engineering in China. Currently, nearly 8,000 papers have been already published. There are around 3,000 papers contributed to the journal each year, but only around 600 of them will be accepted. Transactions of CSAM focuses on a wide range of agricultural machinery, irrigation, electronics, robotics, agro-products engineering, biological energy, agricultural structures and environment and more. Subjects in Transactions of the CSAM have been embodied by many internationally well-known index systems, such as: EI Compendex, CA, CSA, etc.

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