中文摘要：

针对动物体型参数人工测量工作量大、精度低、应激大等问题，以120日龄长白猪标本为研究对象，利用逆向工程技术，通过激光三维扫描仪，采用三角测距原理，计算了目标点三维坐标数据，获取了猪体点云数据。通过Polygon Editing Tool Vel．2．40软件，进行点云数据预处理，基于不规则三角网，重构了猪体的三维曲面模型。进而提取了猪体的体长、体宽、臀宽、体高、臀高、胸围、体表面积、体积等体型参数。结果表明：通过激光三维扫描仪，获取了272021个点数据，重构了猪体三维曲面模型，包含544042个多边形；对比分析三维模型的体型参数检测值与实测值，其体长、体宽、臀宽、体高、臀高、胸围等体型参数检测最大相对误差仅为0．42％，平均相对误差为0．17％。该方法测算精度高，工作量少，且对猪体无应激，可为猪体质量估测模型提供高精度体尺数据支持，也可为动物体型其他参数获取提供技术参考。

英文摘要：

The traditional manual measurement to get the animal growth parameters is high workload, low precision, stress and other issues. For these problems, 120-day-old Landrace samples were chosen for the study, and then got the point cloud data of the pig through the three-dimensional laser scanner, based on the triangulation principle to calculate three-dimensional coordinates of the target point. By Polygon Editing Tool Vel. 2.40 software, the point cloud data were preprocessed, and then the three-dimensional surface model of pig body was reconstructed based on triangulated irregular network. Then the parameters were extracted for pig body length, body width, hip width, height, hip height, chest measurement, body surface area, volume and so on. The results indicated that the 272 021 pig point data were acquired by three-dimensional laser scanner, and pig three-dimensional surface was reconstructed by 544 042 polygons. By error test method, the detection values by the three-dimensional model and measured values of the body parameter were compared. The regression analysis showed that there was high detection precision in body length, width, hip width, height, hip height, chest and other body parameters. The maximum relative error was only 0.42% , and the average relative error was 0.17%. Using the point cloud data of pig and three-dimensional surface of pig to estimation the shape parameters has high precision and can reduce the workload and give no stress in pigs. It can provide high-precision body size data for estimation model of pig body weight, and technical reference for the other parameters of animal body.