刀具磨损图像视差图的非标定方法

朱爱斌; 何大勇; 邹超; 陈渭

doi:10.7652/xjtuxb201603002

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刀具磨损图像视差图的非标定方法

更新时间：2025-07-09

- 刀具磨损图像视差图的非标定方法
- Uncalibrated Method for Disparity Map of Tool Wear Images
- 西安交通大学学报 2016年50卷第3期页码：8-15
- 作者机构：
  
  西安交通大学现代设计及转子轴承系统教育部重点实验室,西安,710049
- 作者简介：
- 基金信息：
  
  : 2015-09-18。作者简介: 朱爱斌(1975—),男,副教授。基金项目: 国家自然科学基金资助项目(51175409)
- DOI：10.7652/xjtuxb201603002
  中图分类号： TH113.2
- 网络首发：2016-03-10，
  
  纸质出版：2016
- 稿件说明：
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朱爱斌, 何大勇, 邹超, 等. 刀具磨损图像视差图的非标定方法[J]. 西安交通大学学报, 2016,50(3):8-15.

Uncalibrated Method for Disparity Map of Tool Wear Images[J]. 2016, 50(3): 8-15.
朱爱斌, 何大勇, 邹超, 等. 刀具磨损图像视差图的非标定方法[J]. 西安交通大学学报, 2016,50(3):8-15. DOI： 10.7652/xjtuxb201603002.

Uncalibrated Method for Disparity Map of Tool Wear Images[J]. 2016, 50(3): 8-15. DOI： 10.7652/xjtuxb201603002.

摘要

刀具磨损检测的视场范围很小、现场工况复杂(存在机床护罩和刀具保持架的遮挡)

而以往对摄像机进行标定的方法多用于大视场环境

并不适合于加工现场的刀具磨损检测。为此

文中提出一种采用非标定双目视觉方法获取刀具磨损图像视差图的方法

无需标定参考物和人工干预。首先

利用SURF(speeded-up robust features)算法检测图像对中的特征点; 其次

利用8点算法计算基本矩阵

再利用极点无穷远变换完成图像对的校正; 最后

利用基本区域匹配方法完成图像对视差的计算。进行了加工现场的磨损刀具图像获取实验

先对比了重构出的刀具视差图轮廓与实际轮廓

接着分析了刀具视差图的精度。结果显示

重构轮廓与实际轮廓基本相符

重构出的视差图的绝对误差在5个像素点以下

相对误差在10%至30%之间

说明在小视场和复杂工况下

用非标定方法获取的刀具视差图能够满足现场检测的精度要求

并且该方法具有灵活和高效的特点。

Abstract

The field of view of tool wear detection is small

and the site condition is complex(e.g.

the blocking of machine cover and tool holder exists). Whereas the traditional method that needs camera calibration is mostly used in large field of view

which is not suitable for on-site tool wear detection. An uncalibrated method based on binocular vision is proposed in this paper for obtaining the disparity map of tool wear images without calibration reference or man-induced intervention. Firstly

SURF(speeded-up robust features)algorithm is used to detect the images' feature points. Then

the 8-point algorithm is adopted to estimate the fundamental matrix; next

image correction is completed by pole infinity transform. Finally

the disparity map is obtained by basic block matching algorithm. On-site experiments were conducted to obtain the tool wear images

and the analysis on profile and accuracy of the reconstructed disparity map was performed. The results show that the reconstructed profile is basically consistent with the actual profile; the absolute error of the reconstructed disparity map is less than 5 pixels and the relative error is between 10% and 30%

meaning that the disparity map obtained by the uncalibrated method in small field of view and complex site condition can meet the accuracy requirement for on-site detection

and this method is also flexible and effective.

关键词

Keywords

references

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