Reconstruction and Body Size Detection of 3D Sheep Body Model Based on Point Cloud Data
Aiming at the high workload, low precision, strong stress of the traditional manual measurement to obtain the sheep growth parameters, a novel measurement technology was proposed. The specimen of the Sunite sheep about 2–3 years old were chosen for study. By reverse engineering technology, point cloud data of sheep was captured by the 3D laser scanner. Because of noise point cloud data, the improved algorithm of k-nearest neighbor was used to process the data. To improve the subsequent processing time and efficiency, octree coding was employed to reduce data, which can get evenly distribution of point cloud data and retain sheep features. Then, 3D surface model of sheep body was reconstructed using Delaunay triangulation. Some parameters were extracted, including sheep body length, body height, hip height, hip width and chest width. Compared actual parameters values with computing values of two ways, by Geomagic platform and the proposed algorithms on the Matlab, average relative errors of two ways were 1.23% and 1.01%, respectively. So results of the proposed algorithm were with small error range. Using the point clouds can reconstruct sheep surface for computing body size without stress.
KeywordsSheep body parameters Point clouds Octree coding Three-dimensional reconstruction Data pretreatment
This work was supported by national and international scientific and technological cooperation special projects (No. 2015DFA00530), supported by national natural science foundation of China (No. 61461041).
- 1.Zhang, L., et al.: Advances in body size measurement and conformation appraisal for sheep. Trans. Chin. Soc. Agric. Eng. 32, 190–197 (2016)Google Scholar
- 2.Zhen, Y., et al.: 3D synchronization imaging system for linear appraisal of dairy cow conformation. Trans. Chin. Soc. Agric. Mach. 40(2), 175–179 (2009)Google Scholar
- 6.Zhang, L., et al.: Design and experiment of non-stress measuring system for sheep’s conformation parameters. Trans. Chin. Soc. Agric. Mach. 47(11), 307–315 (2016)Google Scholar
- 10.Liu, T., et al.: Reconstruction and application of 3D pig body model based on point cloud data. Nongye Jixie Xuebao/Trans. Chin. Soc. Agric. Mach. 45(6), 291–295 (2014)Google Scholar
- 12.Zhang, B., et al.: Feature detection and three-dimensional reconstruction for papaya harvesting. J. Agric. Mech. Res. 12, 212–216 (2016)Google Scholar
- 13.Yu, D.M., et al.: Reconstructing of prototype surface with reverse engineering and data process technology. Key Eng. Mater. 458(458), 368–373 (2011)Google Scholar
- 14.Zhang, Q.F., Sun, X.S.: Measuring principle and developmental prospect of 3D laser scanner. Beijing Surv. Mapp. 1, 39–42 (2011)Google Scholar
- 15.Fang, F., Cheng, X.: A fast data reduction method for massive scattered point clouds based on slicing. Geomat. Inf. Sci. Wuhan Univ. 38(11), 1353–1357 (2013)Google Scholar
- 16.Wang Chunlan, X.H., Jiang, X., Zhou, Y.: The research of removing stray noise fast from point cloud data of three dimension. J. Inner Mongolia Agric. Univ. 38(1), 93–97 (2017)Google Scholar
- 19.Romanoni, A., et al.: Automatic 3D reconstruction of manifold meshes via delaunay triangulation and mesh sweeping, pp. 1–8 (2016)Google Scholar