张旭东,康熙,马丽,刘刚.基于热红外图像的奶牛乳房炎自动检测方法[J].农业机械学报,2019,50(Supp):248-255,282.
ZHANG Xudong,KANG Xi,MA Li,LIU Gang.Automatic Detection Method of Dairy Cow Mastitis Based on Thermal Infrared Image[J].Transactions of the Chinese Society for Agricultural Machinery,2019,50(Supp):248-255,282.
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基于热红外图像的奶牛乳房炎自动检测方法   [下载全文]
Automatic Detection Method of Dairy Cow Mastitis Based on Thermal Infrared Image   [Download Pdf][in English]
投稿时间:2019-04-15  
DOI:10.6041/j.issn.1000-1298.2019.S0.039
中文关键词:  奶牛  乳房炎; 热红外图像; 图像处理; 温度分析
基金项目:国家重点研发计划项目(2018YFD0500705-2018YFD050070502)
作者单位
张旭东 中国农业大学 
康熙 中国农业大学 
马丽 中国农业大学 
刘刚 中国农业大学 
中文摘要:为了提高奶牛乳房炎的检测精度,利用热红外图像测量奶牛关键部位温度,提出了一种奶牛眼睛和乳房自动定位算法。首先对奶牛热红外图像的灰度直方图进行分析,然后提取阈值分割后图像中的HSV(Hue, Saturation, Value)颜色特征和骨架特征,并基于HSV自动检测奶牛眼睛位置,计算骨架特征向量,用支持向量机(Support vector machine,SVM)分类技术自动检测奶牛乳房位置。为了验证定位算法的有效性,对随机选取的40头自然行走的奶牛进行试验验证,结果表明,本文提出的定位算法可以有效定位奶牛眼睛、乳房位置,其定位误差在20像素以内的视频帧识别精度为6867%。根据定位算法所获取的奶牛眼睛和乳房的温度差值进行奶牛乳房炎检测试验,通过温度阈值对奶牛乳房炎发病程度进行评级,并与体细胞计数法(Somatic cell count,SCC)检测结果进行对比,结果表明,等级1检测准确率为33.3%,等级2检测准确率为87.5%。本文研究结果能较准确获取奶牛自然行走状况下眼睛和乳房的位置和温度。
ZHANG Xudong  KANG Xi  MA Li  LIU Gang
China Agricultural University,China Agricultural University,China Agricultural University and China Agricultural University
Key Words:dairy cow  mastitis  thermal infrared image  image processing  temperature analysis
Abstract:In order to improve the detection accuracy of cow mastitis, an automatic eye and breast location method was proposed by using thermal infrared imaging technology to measure the temperature of key parts of cow. The gray scale histogram of the thermal infrared image of dairy cows was firstly analyzed, and then the HSV color features and skeleton features in the threshold segmentation images were extracted. Then, the eye position of dairy cows was automatically detected based on the HSV (Hue, Saturation, Value), and the skeleton feature vector was calculated, which was used to classify and automatically detect the breast position by the support vector machine. In order to verify the effectiveness of the positioning algorithm, totally 40 randomly selected naturally walking cows were verified. The test results showed that the positioning algorithm proposed could effectively locate the eyes and breasts of cows, and the accuracy of video frame recognition within the positioning error of 20 pixels was 68.67%. The cow eyes obtained according to the positioning algorithm was carried out on the temperature difference value of breast milk cow mastitis test, rating by temperature threshold and degree of dairy cow mastitis morbidity and somatic cell count method, comparing the test results it was showed that the rating 1 detection accuracy was 33.3%, the rating 2 detection accuracy was 87.5%. The results of this study can accurately obtain the position and temperature of the eyes and breast under the natural walking condition.

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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