A calibration method of line-structured light system for measuring outer circle dimension during machining

被引:2
作者
Dai, Guanghui [1 ]
Zhang, Qingqing [1 ]
Xu, Xueyan [1 ]
Zhao, Bao [2 ]
机构
[1] Chaohu Univ, Sch Mech Engn, Hefei 238000, Peoples R China
[2] Anhui Univ, Sch Internet, Hefei, Peoples R China
基金
中国国家自然科学基金;
关键词
Machine vision; Line -structured light system; System calibration; 3D profile measurement; Cubic spline interpolation; RECONSTRUCTION;
D O I
10.1016/j.rineng.2024.102525
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
The line-structured light system is widely utilized for various 3D profile measurements due to its convenience and high efficiency. However, the existing calibration methods primarily focus on establishing the relationship between object points and image points, which imposes stringent requirements on the calibration target. To address this issue, a practical calibration method based on interpolation function is proposed in order to measure a specific 3D profile - namely, the diameter of a rotating workpiece during machining. Firstly, the light stripe projected onto an ordinary machined workpiece by a light plane is captured using a Charge-Coupled Device (CCD) camera and subsequently fitted to a quadratic elliptic curve after undergoing image processing. Subsequently, the cubic spline interpolation function is selected to directly establish a mapping relationship between geometric characteristics of the elliptic curve and the diameter measurement. Several experiments are conducted to evaluate the proposed methods. The experimental results demonstrate that compared with two comparison methods, our approach reduces the calibration error of linear structured light systems by 69 % and 51 %, respectively; furthermore, it enables restoration of smooth and detailed 3D models through parallel movement of the system. Moreover, our entire calibration process proves practicable in simplifying experimental procedures while remaining suitable for industrial inspection applications.
引用
收藏
页数:7
相关论文
共 24 条
[1]  
[Anonymous], 2008, Mathematical Methods in Computer Vision
[2]  
Cui Ximin, 2014, Science & Technology Review, V32, P64, DOI 10.3981/j.issn.1000-7857.2014.24.010
[3]   3-D shape reconstruction in an active stereo vision system using genetic algorithms [J].
Dipanda, A ;
Woo, S ;
Marzani, F ;
Bilbault, JM .
PATTERN RECOGNITION, 2003, 36 (09) :2143-2159
[4]   3D measurement of gears based on a line structured light sensor [J].
Guo, Xiaozhong ;
Shi, Zhaoyao ;
Yu, Bo ;
Zhao, Baoya ;
Li, Ke ;
Sun, Yanqiang .
PRECISION ENGINEERING-JOURNAL OF THE INTERNATIONAL SOCIETIES FOR PRECISION ENGINEERING AND NANOTECHNOLOGY, 2020, 61 :160-169
[5]   Energy consumption prediction in water treatment plants using deep learning with data augmentation [J].
Harrou, Fouzi ;
Dairi, Abdelkader ;
Dorbane, Abdelhakim ;
Sun, Ying .
RESULTS IN ENGINEERING, 2023, 20
[6]   Calibrating a structured light stripe system: A novel approach [J].
Huynh, DQ ;
Owens, RA ;
Hartmann, PE .
INTERNATIONAL JOURNAL OF COMPUTER VISION, 1999, 33 (01) :73-86
[7]  
Li P., 2017, Infrared Laser Eng., V46
[8]   A calibration method for line-structured light system by using sinusoidal fringes and homography matrix [J].
Ping, Yishan ;
Liu, Yuankun .
OPTIK, 2022, 261
[9]  
Quang Thinh Ngo H., 2024, Results in Engineering, V2024
[10]   Support vector machines for 3D shape processing [J].
Steinke, F ;
Schölkopf, B ;
Blanz, V .
COMPUTER GRAPHICS FORUM, 2005, 24 (03) :285-294