| 一种板型物体混叠场景的快速分割算法 | |
| Alternative Title | A Fast Segmenting Method for Scenes with Stacked Plate-Shaped Objects |
鲁荣荣1,2,3,4,5 ; 朱枫1,2,4,5; 吴清潇1,2,4,5; 崔芸阁1,2,3,4,5; 孔研自1,2,3,4,5; 陈佛计1,2,3,4,5
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| Department | 光电信息技术研究室 |
| Source Publication | 光学学报
 |
| ISSN | 0253-2239 |
| 2019 | |
| Volume | 39Issue:4Pages:1-10 |
| Indexed By | EI ; CSCD |
| EI Accession number | 20192006931102 |
| CSCD ID | CSCD:6488373 |
| Contribution Rank | 1 |
| Funding Organization | 国家自然科学基金(U1713216) ; 机器人学国家重点实验室自主课题(2017-Z21) |
| Keyword | 机器视觉 点云分割 深度图 随机采样一致性算法 |
| Abstract | 针对多个板型物体混叠摆放的场景,本文提出了一种快速有效的分割方法。算法充分利用有序点云的特点,将自顶向下以及自底向上的分割策略有机结合。首先,根据三维点的空间位置和法向量信息,利用随机采样一致性算法从三维点云数据中快速提取平面点集。然后将提取的平面点集所对应的图像坐标映射为二值图像,通过连通区域分析将其分割为多个连通的平面区域。接着利用“胶水”算法对这些区域进行快速合并,并对较大的弱连接连通区域进行断裂修正,从而得到最终的分割结果。实验结果表明,本文提出的方法快速有效。与区域生长算法相比,本文方法分割结果更优,且算法效率大幅提升。 |
| Other Abstract | A fast and efficient segmentation algorithm is proposed for scenes in which multiple plate-shaped objects are placed in an overlapping manner. The algorithm makes full use of the characteristics of the ordered point cloud, and combines the top-down and bottom-up segmentation strategies. The Random Sample Consensus (RANSAC) algorithm is used to quickly extract the three-dimensional planar point set according to the spatial position and normal vector of the three-dimensional point from the three-dimensional point cloud. The image coordinates corresponding to the extracted planar point set are mapped into a binary image, and are divided into a plurality of connected planar regions by the connected region analysis. Then, the glue algorithm is used to quickly merge these regions, and the larger weakly connected regions are subjected to the fracture correction, so as to obtain the final segmentation result. The experimental results show that compared with the region growing algorithm, the proposed algorithm can obtain better segmentation results, and the algorithm efficiency is greatly improved. |
| Language | 中文 |
| Citation statistics | |
| Document Type | 期刊论文 |
| Identifier | http://ir.sia.cn/handle/173321/23802 |
| Collection | 光电信息技术研究室 |
| Corresponding Author | 朱枫 |
| Affiliation | 1.中国科学院沈阳自动化研究所 2.中国科学院机器人与智能制造创新研究院 3.中国科学院大学 4.中国科学院光电信息处理重点实验室 5.辽宁省图像理解与视觉计算重点实验室 |
| Recommended Citation GB/T 7714 | 鲁荣荣,朱枫,吴清潇,等. 一种板型物体混叠场景的快速分割算法[J]. 光学学报,2019,39(4):1-10. |
| APA | 鲁荣荣,朱枫,吴清潇,崔芸阁,孔研自,&陈佛计.(2019).一种板型物体混叠场景的快速分割算法.光学学报,39(4),1-10. |
| MLA | 鲁荣荣,et al."一种板型物体混叠场景的快速分割算法".光学学报 39.4(2019):1-10. |
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| 一种板型物体混叠场景的快速分割算法.pd（1655KB） | 期刊论文 | 作者接受稿 | 开放获取 | CC BY-NC-SA | View Download | |
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