|Table of Contents|

[1] Zhang Zhisheng, He Boxia, Dai Min, Shi Jinfei, et al. Feature-based sequential partial vision measurement methodfor large scale machine parts [J]. Journal of Southeast University (English Edition), 2007, 23 (4): 550-555. [doi:10.3969/j.issn.1003-7985.2007.04.015]
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Feature-based sequential partial vision measurement methodfor large scale machine parts()
基于特征的大尺寸零件序列局部视觉测量方法

Journal of Southeast University (English Edition)[ISSN:1003-7985/CN:32-1325/N]

Volumn:
23
Issue:
2007 4
Page:
550-555
Research Field:
Automation
Publishing date:
2007-12-30

Info

Title:
Feature-based sequential partial vision measurement methodfor large scale machine parts
基于特征的大尺寸零件序列局部视觉测量方法
Author(s):
Zhang Zhisheng, He Boxia, Dai Min, Shi Jinfei
School of Mechanical Engineering, Southeast University, Nanjing 211189, China
张志胜, 何博侠, 戴敏, 史金飞
东南大学机械工程学院, 南京 211189
Keywords:
vision measurement sequential image texture feature feature matching
视觉测量 序列图像 表面纹理 特征匹配
PACS:
TP274.5;TG806
DOI:
10.3969/j.issn.1003-7985.2007.04.015
Abstract:
To realize the high-precision vision measurement for large scale machine parts, a new vision measurement method based on dimension features of sequential partial images is proposed.Instead of mosaicking the partial images, extracting the dimension features of the sequential partial images and deriving the part size according to the relationships between the sequential images is a novel method to realize the high-precision and fast measurement of machine parts.To overcome the corresponding problems arising from the relative rotation between two sequential partial images, a rectifying method based on texture features is put forward to effectively improve the processing speed.Finally, a case study is provided to demonstrate the analysis procedure and the effectiveness of the proposed method.The experiments show that the relative error is less than 0.012% using the sequential image measurement method to gauge large scale straight-edge parts.The measurement precision meets the needs of precise measurement for sheet metal parts.
为了实现常规尺寸和大尺寸机械零件的视觉测量, 提出一种新的基于序列局部图像尺寸特征的测量方法.不进行图像拼接, 而是提取序列局部图像的尺寸特征, 并以图像序列之间的关联关系为依据求解零件尺寸.针对影响测量精度的相面旋转问题, 充分利用工件表面纹理信息, 提出了基于纹理特征的序列局部图像校准方法, 获得序列图像之间的相对旋转角度, 解决了测量过程中相机抖动或零件旋转引起的尺寸特征方向变动问题.通过实例说明了所提方法的实现过程及其有效性.实验表明, 对大尺寸零件采用序列图像测量法, 相对测量误差在0.012%以内, 满足板类零件的精密测量要求.

References:

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Memo

Memo:
Biography: Zhang Zhisheng(1974—), male, doctor, associate professor, oldbc@seu.edu.cn.
Last Update: 2007-12-20