A high dynamic range structured light means for the 3D measurement of specular surface

Abstract This paper presents a novel structured light approach for the 3D reconstruction of specular surface. The binary shifting strip is adopted as structured light pattern instead of conventional sinusoidal pattern. Based on the framework of conventional High Dynamic Range (HDR) imaging technique, an efficient means is first introduced to estimate the camera response function. And then, dynamic range of the generated radiance map is compressed in the gradient domain by introducing an attenuation function. Subject to the change of lighting conditions caused by projecting different structured light patterns, the structure light image with middle exposure level is selected as the reference image and used for the slight adjustment of the primary fused image. Finally, the regenerated structured light images with well exposing condition are used for 3D reconstruction of the specular surface. To evaluate performance of the method, some stainless stamping parts with strong reflectivity are used for the experiments. And the results showed that, different specular targets with various shapes can be precisely reconstructed by the proposed method.

[1]  Dani Lischinski,et al.  Gradient Domain High Dynamic Range Compression , 2023 .

[2]  Chenggen Quan,et al.  A modified phase-coding method for absolute phase retrieval , 2016 .

[3]  Song Zhang,et al.  High dynamic range real-time 3D shape measurement. , 2016, Optics express.

[4]  Konstantinos Falaggis,et al.  Absolute phase recovery in structured light illumination systems: Sinusoidal vs. intensity discrete patterns , 2016 .

[5]  Jens Guehring,et al.  Dense 3D surface acquisition by structured light using off-the-shelf components , 2000, IS&T/SPIE Electronic Imaging.

[6]  Shree K. Nayar,et al.  Diffuse structured light , 2012, 2012 IEEE International Conference on Computational Photography (ICCP).

[7]  Jing Xu,et al.  A Robust Surface Coding Method for Optically Challenging Objects Using Structured Light , 2014, IEEE Transactions on Automation Science and Engineering.

[8]  Wei Yang,et al.  Robust and Accurate Surface Measurement Using Structured Light , 2008, IEEE Transactions on Instrumentation and Measurement.

[9]  Shree K. Nayar,et al.  A Theory of Specular Surface Geometry , 2004, International Journal of Computer Vision.

[10]  Jian Chen,et al.  A robust method to extract a laser stripe centre based on grey level moment , 2015 .

[11]  Joaquim Salvi,et al.  A state of the art in structured light patterns for surface profilometry , 2010, Pattern Recognit..

[12]  Luc Van Gool,et al.  Scene-adapted structured light , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).

[13]  Jitendra Malik,et al.  Recovering high dynamic range radiance maps from photographs , 1997, SIGGRAPH '08.

[14]  Andrew Zisserman,et al.  Multiple View Geometry in Computer Vision (2nd ed) , 2003 .

[15]  Norihiro Abe,et al.  3D Surface Estimation and Model Construction From Specular Motion in Image Sequences , 1997, IEEE Trans. Pattern Anal. Mach. Intell..

[16]  Hans-Peter Seidel,et al.  3D acquisition of mirroring objects using striped patterns , 2005, Graph. Model..

[17]  Giovanna Sansoni,et al.  Calibration and performance evaluation of a 3-D imaging sensor based on the projection of structured light , 2000, IEEE Trans. Instrum. Meas..

[18]  Guangjun Zhang,et al.  On-site calibration method for outdoor binocular stereo vision sensors , 2016 .

[19]  Pau Gargallo,et al.  General Specular Surface Triangulation , 2006, ACCV.

[20]  Song Zhang,et al.  High dynamic range scanning technique , 2009 .

[21]  Gene H. Golub,et al.  Matrix computations , 1983 .

[22]  Sam Van der Jeught,et al.  Real-time structured light profilometry: a review , 2016 .

[23]  Jiang Yu Zheng,et al.  Acquiring a Complete 3D Model from Specular Motion under the Illumination of Circular-Shaped Light Sources , 2000, IEEE Trans. Pattern Anal. Mach. Intell..

[24]  Alessandro Ferrero,et al.  Camera as the instrument: the rising trend of vision based measurement , 2014, IEEE Instrumentation & Measurement Magazine.

[25]  Ronald Chung,et al.  Use of LCD Panel for Calibrating Structured-Light-Based Range Sensing System , 2008, IEEE Transactions on Instrumentation and Measurement.

[26]  Hongzhi Jiang,et al.  High dynamic range fringe acquisition: A novel 3-D scanning technique for high-reflective surfaces , 2012 .

[27]  Takeshi Hashimoto,et al.  Gradient-Based Synthesized Multiple Exposure Time Color HDR Image , 2008, IEEE Transactions on Instrumentation and Measurement.

[28]  Hui Lin,et al.  Adaptive digital fringe projection technique for high dynamic range three-dimensional shape measurement. , 2016, Optics express.

[29]  Song Zhang Recent progresses on real-time 3D shape measurement using digital fringe projection techniques , 2010 .

[30]  Shijie Feng,et al.  General solution for high dynamic range three-dimensional shape measurement using the fringe projection technique , 2014 .

[31]  Ronald Chung,et al.  An Accurate and Robust Strip-Edge-Based Structured Light Means for Shiny Surface Micromeasurement in 3-D , 2013, IEEE Transactions on Industrial Electronics.