基于双目深度估计的牛体尺测量方法设计北大核心CSCD

为解决传统人工接触式测量工作量大、测量条件相对艰苦及影响牛正常生活习性的繁琐问题,提出了基于目标检测的双目深度估计牛的体尺测量方法。首先,通过双目相机采集图片,利用YOLOv5(you only look once v5)目标检测算法检测图像中的体尺特征部位,结合边缘检测等算法获取牛体尺测点。其次,利用双目立体匹配算法将双目2维图片转化为空间3维深度信息图,在深度信息图上读取测点3维坐标。最后,在3维坐标系下运用空间欧氏距离进而计算牛的体尺参数。搭建了测试平台进行测量,实验结果表明,该方法的测量精度高于现有相关方法,其中体长的平均相对误差为2.4%、体高的平均相对误差为1.1%、体斜长的平均相对误差为3.3%,为牛体尺测量提供了可行的示范。

Design of the measurement method of cow body size based on binocular depth estimation

In order to solve the tedious problems of traditional manual contact me asurement with large workload, relatively difficult measurement conditions and affecting the normal living habi ts of cattle,a method for measuring cattle body size based on binocular depth estimation with target detection is pr oposed.Firstly,the images are collected by a binocular camera,and the object detection algorithm YOLOv5(you on ly look once v5) is used to detect the feature parts of the body scale in the images,and combined with edge det ection and other algorithms to obtain the cattle body scale measurement points.Secondly,the binocular stereo matchin g algorithm is used to transform the binocular two-dimensional images into a spatial three-dimensional depth in formation map,and the three- dimensional coordinates of the measurement points are read on the depth informat ion map.Finally,the spatial Euclidean distance is used to calculate parameters of the cattle body scale in three-dimensional coordinate system.A test platform is built for the measurement,and the experimental resul ts show that the measurement accuracy of the method is higher than the existing related methods,in which the average relative error of body length is 2.4%,the average relative error of body height is 5.9%,and the avera ge relative error of the body oblique length is 3.3%,which provide a feasible demonstration for the measurement of ca ttle body scale.