基于坐标轴投影勘察的深度图像树型分割

赵翠莲; 施晓磊; 荣坚; 范志坚

doi:10.3788/OPE.20111906.1430

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基于坐标轴投影勘察的深度图像树型分割

信息科学 | 更新时间：2020-08-12

- 基于坐标轴投影勘察的深度图像树型分割
- Tree-type segmentation of range images by exploration of coordinate-axis projection
- 光学精密工程 2011年19卷第6期页码：1430-1435
- 作者机构：
  
  上海大学上海市机械自动化及机器人重点实验室上海,200072
- 作者简介：
- 基金信息：
  
  上海市重点学科建设基金资助项目(No.Y0102)();上海市科委重点科技攻关项目(No.08511501100)()
- DOI：10.3788/OPE.20111906.1430
  中图分类号： TP391.4
- 收稿日期：2010-06-25，
  
  修回日期：2010-09-13，
  
  网络出版日期：2011-06-25，
  
  纸质出版日期：2011-06-25
- 稿件说明：
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赵翠莲, 施晓磊, 荣坚, 范志坚. 基于坐标轴投影勘察的深度图像树型分割[J]. 光学精密工程, 2011,19(6): 1430-1435

ZHAO Cui-lian, SHI Xiao-lei, RONG Jian, FAN Zhi-jian. Tree-type segmentation of range images by exploration of coordinate-axis projection[J]. Editorial Office of Optics and Precision Engineering, 2011,19(6): 1430-1435
赵翠莲, 施晓磊, 荣坚, 范志坚. 基于坐标轴投影勘察的深度图像树型分割[J]. 光学精密工程, 2011,19(6): 1430-1435 DOI： 10.3788/OPE.20111906.1430.

ZHAO Cui-lian, SHI Xiao-lei, RONG Jian, FAN Zhi-jian. Tree-type segmentation of range images by exploration of coordinate-axis projection[J]. Editorial Office of Optics and Precision Engineering, 2011,19(6): 1430-1435 DOI： 10.3788/OPE.20111906.1430.

摘要

针对具有空间连通域特征的深度图像

提出了一种基于坐标轴投影勘察的树型分割方法。通过投影勘察实现沿最优投影方向的坐标轴投影

把对深度图像的空间连通域分割转化为对投影在坐标轴上的一维点数据的区间连通域分割

最终利用树型结构实现分割。将该方法应用于实际深度图像的分割

并分别对理想和极端两种情况下的分割结果进行了讨论。结果表明

算法对具有空间连通域特征的深度图像的分割行之有效

并且在相同的硬件平台上对不同深度图像具有基本恒定的分割速度。对于分别包含19 792、35 186、79 618个点的深度图像

理想和极端情况下的平均分割速度分别为每万点0.168 s和0.494 s

具有较高的分割效率。

Abstract

A tree-type segmentation method based on the exploration of projection onto coordinate axes was proposed for range images with a feature of spatial connective region. By implementing the projections onto coordinate axes at the optimum angle by the exploration of projection

the segmentation of range images was transformed into the segmentation of 1D point data projected onto coordinate axes.Finally

a tree-type structure was employed to carry out the process of segmentation. The algorithm was applied to the range images acquired from a concrete project to verify the effectiveness and the efficiency

and the results of both ideal and extreme conditions were discussed

respectively. The results show that the algorithm can effectively segment range images with the feature of spatial connective region and has a constant speed of segmentation with regard to different range images in the same hardware platform. For the 3 tested range images containing 19 792

35 186 and 79 618 points

the average speeds of segmentation in ideal and extreme conditions are 0.168 s and 0.494 s every 10 000 points

respectively

which verifies the high effectiveness and efficiency of segmentation.

关键词

Keywords

references

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