摘要
To solve the problem of automatic tube structure recognition, a recognition method for complex tube structures based on local shape feature was proposed. The recognition method first obtained the different tube structures' shape. Then the obtained shape was converted to a signal by shape descriptor. Batches of signal samples was collected and applied to train a BP neural network to classify the different tube structures. The training experiments showed that the recognition method had accuracy in 97%. In a certain application, multi-cameras were applied to recognize the tube structures and a voting method was also applied to increase the accuracy, which could be applied to reconstruct and measure multi-branch tubes automatically.
| 投稿的翻译标题 | Recognition method for complex tube structures based on local shape feature |
|---|---|
| 源语言 | 繁体中文 |
| 页（从-至） | 598-606 |
| 页数 | 9 |
| 期刊 | Jisuanji Jicheng Zhizao Xitong/Computer Integrated Manufacturing Systems, CIMS |
| 卷 | 25 |
| 期 | 3 |
| DOI | |
| 出版状态 | 已出版 - 1 3月 2019 |
关键词
- Back propagation
- Local shape feature
- Machine vision
- Neural network
- Shape descriptor
- Tube measurement
- Tube structures
指纹
探究 '基于局部轮廓形状特征的复杂管路结构识别方法' 的科研主题。它们共同构成独一无二的指纹。引用此
Huang, H., Liu, S., Liu, J., Wang, X., & Jin, P. (2019). 基于局部轮廓形状特征的复杂管路结构识别方法. Jisuanji Jicheng Zhizao Xitong/Computer Integrated Manufacturing Systems, CIMS, 25(3), 598-606. https://doi.org/10.13196/j.cims.2019.03.007