May 2017

Article Contents

Chinese Optics> 2017> 10(3): 348-354.

WANG Ya-nan, WANG Ting-feng, TIAN Yu-zhen, SUN Tao. Improved local convexity algorithm of segmentation for 3D point cloud[J]. Chinese Optics, 2017, 10(3): 348-354. doi: 10.3788/CO.20171003.0348

Citation:

WANG Ya-nan, WANG Ting-feng, TIAN Yu-zhen, SUN Tao. Improved local convexity algorithm of segmentation for 3D point cloud[J].Chinese Optics, 2017, 10(3): 348-354.doi:10.3788/CO.20171003.0348

WANG Ya-nan, WANG Ting-feng, TIAN Yu-zhen, SUN Tao. Improved local convexity algorithm of segmentation for 3D point cloud[J]. Chinese Optics, 2017, 10(3): 348-354. doi: 10.3788/CO.20171003.0348

Citation:

WANG Ya-nan, WANG Ting-feng, TIAN Yu-zhen, SUN Tao. Improved local convexity algorithm of segmentation for 3D point cloud[J].Chinese Optics, 2017, 10(3): 348-354.doi:10.3788/CO.20171003.0348

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Improved local convexity algorithm of segmentation for 3D point cloud

doi:10.3788/CO.20171003.0348

1.
State Key Laboratory of Laser Interaction with Matter, Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun 130033, China
2.
University of Chinese Academy of Science, Beijing 100049, China

Funds:

Supported by National High-tech R & D Program of China

Received Date:23 Jan 2017
Rev Recd Date:30 Mar 2017
Publish Date:01 Jun 2017

Abstract

Abstract

Segmentation for point cloud is the basis of classification, recognition and reconstruction of point cloud datasets and the segmentation result plays an important role in following research. In this paper, we propose a method using connected point sets to analyze and improve the relationship between adjacent points in the local convexity segmentation, to solve problems of oversegmentation and undersegmentation when using the existing algorithms to segment scattered point cloud data in complex environment in 3D laser imaging system. By this method we use the main vertex and neighbors to constitute connected point sets which can be local point subsets of segmentation and form the effective segmented regions. The method solves the problem of the irregular object's segmentation, which can not be accomplished by common methods, and improves the accuracy of segmentation. Compared with the min-cut based segmentation and region growing segmentation, the improved local convexity segmentation of connected point sets is better for segmentation results of actual road information, and it can avoid oversegmentation and undersegmentation to some extent. It proved that this method is suitable for segmentation of scattered point cloud data in complex environment.
- three-dimensional laser imaging,
- segmentation for point cloud,
- connected point sets,
- local convexity

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References (16)

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