Instrumentation, Techniques, and Measurement

Online fringe projection profilometry based on scale-invariant feature transform

[+] Author Affiliations
Hongru Li

Sichuan University, College of Electronics and Information Engineering, No. 24 South Section 1, Yihuan Road, Chengdu, Sichuan Province 610065, China

Nanyang Technological University, Centre for Optical and Laser Engineering, School of Mechanical and Aerospace Engineering, 50 Nanyang Avenue, Singapore 639798, Singapore

Guoying Feng, Shouhuan Zhou

Sichuan University, College of Electronics and Information Engineering, No. 24 South Section 1, Yihuan Road, Chengdu, Sichuan Province 610065, China

Peng Yang

Nanyang Technological University, Centre for Optical and Laser Engineering, School of Mechanical and Aerospace Engineering, 50 Nanyang Avenue, Singapore 639798, Singapore

Peking University, Beijing Key Lab of Spatial Information Integration and 3s Application, No. 5 Yiheyuan Road, Haidian District, Beijing 100871, China

Zhaomin Wang

Nanyang Technological University, Centre for Optical and Laser Engineering, School of Mechanical and Aerospace Engineering, 50 Nanyang Avenue, Singapore 639798, Singapore

Ngee Ann Polytechnic, Centre for Applied Photonics and Laser Technology, 535 Clementi Road, Singapore 599489, Singapore

Anand Asundi

Nanyang Technological University, Centre for Optical and Laser Engineering, School of Mechanical and Aerospace Engineering, 50 Nanyang Avenue, Singapore 639798, Singapore

Opt. Eng. 55(8), 084101 (Aug 03, 2016). doi:10.1117/1.OE.55.8.084101
History: Received March 20, 2016; Accepted July 11, 2016
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Abstract.  An online fringe projection profilometry (OFPP) based on scale-invariant feature transform (SIFT) is proposed. Both rotary and linear models are discussed. First, the captured images are enhanced by “retinex” theory for better contrast and an improved reprojection technique is carried out to rectify pixel size while keeping the right aspect ratio. Then the SIFT algorithm with random sample consensus algorithm is used to match feature points between frames. In this process, quick response code is innovatively adopted as a feature pattern as well as object modulation. The characteristic parameters, which include rotation angle in rotary OFPP and rectilinear displacement in linear OFPP, are calculated by a vector-based solution. Moreover, a statistical filter is applied to obtain more accurate values. The equivalent aligned fringe patterns are then extracted from each frame. The equal step algorithm, advanced iterative algorithm, and principal component analysis are eligible for phase retrieval according to whether the object moving direction accords with the fringe direction or not. The three-dimensional profile of the moving object can finally be reconstructed. Numerical simulations and experimental results verified the validity and feasibility of the proposed method.

© 2016 Society of Photo-Optical Instrumentation Engineers

Citation

Hongru Li ; Guoying Feng ; Peng Yang ; Zhaomin Wang ; Shouhuan Zhou, et al.
"Online fringe projection profilometry based on scale-invariant feature transform", Opt. Eng. 55(8), 084101 (Aug 03, 2016). ; http://dx.doi.org/10.1117/1.OE.55.8.084101


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