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Removing Stray Noise Quickly from Point Cloud Data Based on Sheep Model

  • Chunlan Wang
  • Heru XueEmail author
  • Xinhua Jiang
  • Yanqing Zhou
  • Liyan Wang
Conference paper
Part of the IFIP Advances in Information and Communication Technology book series (IFIPAICT, volume 509)

Abstract

The noise data could be produced when we scanned the object by Handy 3D scanner due to human factors, the target surface and the instrument itself factors etc. Noised point cloud data could seriously affect the precision and efficiency of three-dimensional reconstruction in late stage. To this problem, we used the sheep body’s three-dimensional point cloud data and changed the algorithm of k-nearest neighbors and presented method that combined the k-nearest neighbor denoising and median filtering. Firstly, the improved k-nearest neighbors algorithm could establish topology relationship fast, identify and delete some noise data; then, using the filter method processed the point cloud data and all noise data could be identified and deleted. The experimental results show that the method we presented can eliminate the stray noise from the point cloud data quickly and accurately and keep ideal target.

Keywords

Scattered point cloud K-nearest neighbor point Median filtering Outliers Noise data 

Notes

Acknowledgment

This work was partially supported by the National Natural Science Foundation of China(No.61461041).

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Copyright information

© IFIP International Federation for Information Processing 2019

Authors and Affiliations

  • Chunlan Wang
    • 1
  • Heru Xue
    • 1
    Email author
  • Xinhua Jiang
    • 1
  • Yanqing Zhou
    • 1
  • Liyan Wang
    • 1
  1. 1.College of Computer and Information EngineeringInner Mongolia Agricultural UniversityHohhtChina

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