TY - JOUR
T1 - Stereo deflectometry based automatic segmentation technique for measuring structured specular surfaces
AU - Gao, Feng
AU - Xu, Yongjia
AU - Jiang, Jane
N1 - Funding Information:
Feng Gao, Xiangqian Jiang reports financial support was provided by Engineering and Physical Sciences Research Council.
Funding Information:
The authors gratefully acknowledge the UK's Engineering and Physical Sciences Research Council (EPSRC) funding of “The EPSRC Future Advanced Metrology Hub” (EP/P006930/1) and the funding of “A Multiscale Digital Twin-Driven Smart Manufacturing System for High Value-Added Products” (EP/T024844/1).
Publisher Copyright:
© 2022
PY - 2022/11/1
Y1 - 2022/11/1
N2 - Techniques have been studied to extend the measurement capability of stereo deflectometry from continuous specular surfaces only to complex structured specular surfaces. Segmentation is a key process in these techniques, which separates a measured structured surface into several continues segments with gradient and coordinate data to achieve high form measurement accuracy. However, it is a great challenge to achieve automatic, fast, and accurate segmentation since specular surfaces have no RGB (red, greed, and blue) texture to be used in the segmentation process. In this paper, we present an automatic segmentation technique based on the characteristics of gradient variation and 3D coordinate data of the measured structured specular surfaces. Different segmentation strategies are applied and discussed for the measured discontinuous specular surfaces and continuous non-differentiable specular surfaces. Compared with the existing segmentation methods in terms of stereo deflectometry, the proposed technique shows significantly advantages in automation, speed, and flexibility. Experimental results verified the effectiveness and accuracy of the proposed method in the measurement of structured specular surfaces.
AB - Techniques have been studied to extend the measurement capability of stereo deflectometry from continuous specular surfaces only to complex structured specular surfaces. Segmentation is a key process in these techniques, which separates a measured structured surface into several continues segments with gradient and coordinate data to achieve high form measurement accuracy. However, it is a great challenge to achieve automatic, fast, and accurate segmentation since specular surfaces have no RGB (red, greed, and blue) texture to be used in the segmentation process. In this paper, we present an automatic segmentation technique based on the characteristics of gradient variation and 3D coordinate data of the measured structured specular surfaces. Different segmentation strategies are applied and discussed for the measured discontinuous specular surfaces and continuous non-differentiable specular surfaces. Compared with the existing segmentation methods in terms of stereo deflectometry, the proposed technique shows significantly advantages in automation, speed, and flexibility. Experimental results verified the effectiveness and accuracy of the proposed method in the measurement of structured specular surfaces.
KW - Optical metrology
KW - Three-dimensional measurement
KW - Deflectometry
KW - Structured specular surfaces
KW - Data fusion
UR - http://www.scopus.com/inward/record.url?scp=85134680112&partnerID=8YFLogxK
U2 - 10.1016/j.optlaseng.2022.107195
DO - 10.1016/j.optlaseng.2022.107195
M3 - Article
VL - 158
JO - Optics and Lasers in Engineering
JF - Optics and Lasers in Engineering
SN - 0143-8166
M1 - 107195
ER -