Reconstructing Shapes and Appearances of Thin Film Objects Using RGB Images

Reconstruction of shapes and appearances of thin film objects can be applied to many fields such as industrial inspection, biological analysis, and archaeologic research. However, it comes with many challenging issues because the appearances of thin film can change dramatically depending on view and light directions. The appearance is deeply dependent on not only the shapes but also the optical parameters of thin film. In this paper, we propose a novel method to estimate shapes and film thickness. First, we narrow down candidates of zenith angle by degree of polarization and determine it by the intensity of thin film which increases monotonically along the zenith angle. Second, we determine azimuth angle from occluding boundaries. Finally, we estimate the film thickness by comparing a look-up table of color along the thickness and zenith angle with captured images. We experimentally evaluated the accuracy of estimated shapes and appearances and found that our proposed method is effective.

[1]  Katsushi Ikeuchi,et al.  Camera Spectral Sensitivity and White Balance Estimation from Sky Images , 2013, International Journal of Computer Vision.

[2]  Berthold K. P. Horn A problem in computer vision , 1975 .

[3]  Mark S. Drew,et al.  Deriving Spectra from Colors and Rendering Light Interference , 1999, IEEE Computer Graphics and Applications.

[4]  Kristin J. Dana,et al.  Device for convenient measurement of spatially varying bidirectional reflectance. , 2004, Journal of the Optical Society of America. A, Optics, image science, and vision.

[5]  K. Kitagawa,et al.  Transparent film thickness measurement by three-wavelength interference method: An extended application of Global Model Fitting algorithm , 2012, 2012 9th France-Japan & 7th Europe-Asia Congress on Mechatronics (MECATRONICS) / 13th Int'l Workshop on Research and Education in Mechatronics (REM).

[6]  Francisco J. Serón,et al.  Physically-based simulation of rainbows , 2012, TOGS.

[7]  Katsushi Ikeuchi,et al.  Determining Shapes of Transparent Objects from Two Polarization Images , 2002, MVA.

[8]  Shree K. Nayar,et al.  Reflectance and texture of real-world surfaces , 1997, Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[9]  Jason Lawrence,et al.  A coaxial optical scanner for synchronous acquisition of 3D geometry and surface reflectance , 2010, ACM Transactions on Graphics.

[10]  Kiriakos N. Kutulakos,et al.  Reconstructing the Surface of Inhomogeneous Transparent Scenes by Scatter-Trace Photography , 2007, 2007 IEEE 11th International Conference on Computer Vision.

[11]  Kazufumi Kaneda,et al.  An accurate illumination model for objects coated with multilayer films , 2001, Comput. Graph..

[12]  Christian Wöhler,et al.  An introduction to image-based 3D surface reconstruction and a survey of photometric stereo methods , 2011 .

[13]  Katsushi Ikeuchi,et al.  Reconstructing Shape and Appearance of Thin Film Objects with Hyper Spectral Sensor , 2014, ACCV.

[14]  Katsuichi Kitagawa,et al.  Thin-film thickness profile measurement by three-wavelength interference color analysis. , 2013, Applied optics.

[15]  Mark S. Drew,et al.  Rendering Iridescent Colors of Optical Disks , 2000, Rendering Techniques.

[16]  Yasushi Yagi,et al.  Rapid BRDF Measurement Using an Ellipsoidal Mirror and a Projector , 2009, IPSJ Trans. Comput. Vis. Appl..

[17]  Terrance E. Boult,et al.  Constraining Object Features Using a Polarization Reflectance Model , 1991, IEEE Trans. Pattern Anal. Mach. Intell..

[18]  Kazufumi Kaneda,et al.  Rendering iridescent colors appearing on natural objects , 2000, Proceedings the Eighth Pacific Conference on Computer Graphics and Applications.

[19]  Ramesh Raskar,et al.  Reflectance model for diffraction , 2012, TOGS.

[20]  K. Ikeuchi,et al.  Measurement of surface orientations of transparent objects by use of polarization in highlight , 1999 .

[21]  Katsushi Ikeuchi,et al.  Transparent surface modeling from a pair of polarization images , 2004 .

[22]  Karl Wilh. Meissner Interference Spectroscopy. Part II , 1941 .