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Reconstruction and Body Size Detection of 3D Sheep Body Model Based on Point Cloud Data

  • Yanqing Zhou
  • Heru XueEmail author
  • Chunlan Wang
  • Xinhua Jiang
  • Xiaojing Gao
  • Jie Bai
Conference paper
Part of the IFIP Advances in Information and Communication Technology book series (IFIPAICT, volume 546)

Abstract

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.

Keywords

Sheep body parameters Point clouds Octree coding Three-dimensional reconstruction Data pretreatment 

Notes

Acknowledgements

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).

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Copyright information

© IFIP International Federation for Information Processing 2019

Authors and Affiliations

  • Yanqing Zhou
    • 1
  • Heru Xue
    • 1
    Email author
  • Chunlan Wang
    • 1
  • Xinhua Jiang
    • 1
  • Xiaojing Gao
    • 1
  • Jie Bai
    • 1
  1. 1.College of Computer and Information EngineeringInner Mongolia Agricultural UniversityHohhotChina

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