第19卷
第6期
2011年6月
文章编号
1004-924X(2011)06-1430-06
光学精密工程
Optics and Precision Engineering
Vol, 19
No.6 Jun.2011
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
（上海大学上海市机械自动化及机器人重点实验室，上海200072）
摘要：针对具有空间连通坡特征的深度图像，提出了一种基于垒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制转化为对投影在尘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制，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制行之有效，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19792、35186、79618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0.168s和0.494s，具有较高的分割效率。
关键词：深度图像；空间连通城；树型分割；坐标轴；投影勘察
中图分类号：TP391.4
文献标识码：A
doi;10,3788/OPE.20111906.1430
Tree-type segmentation of range images by explorationofcoordinate-axisprojection
ZHAO Cui-lian',SHI Xiao-lei,RONG Jian, FAN Zhi-jian
(ShanghaiKey Laboratory of Mechanical Automation and Robot
ShanghaiUniversity,Shanghai200072,China)
Corresponding author,E-mail;clzhao@mail.shu.edu.cn
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 projec-tions 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 ef-ficiency, and the results of both ideal and extreme conditions were discussed, respectively. The re sults show that the algorithm can effectively segment range images with the feature of spatial connec tive 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 av erage 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
收稿日期：2010-06-25；修订日期：2010-09-13.
基金项目：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）