Specular Highlight Removal for High Reflection Surface with Linear Diffuser

In structured light 3D measurement field, when the object has smooth surface, it can form a highlight area due to the specular reflection, and the distortion of the object will make a large measurement error. In order to solve this problem, this paper use seven steps sine-phase shift combined with linear diffuser to remove highlight. Firstly, the principle of removing specular with diffuser is analyzed, then the overall design of the system is introduced, which includes 3D reconstruction and system calibration method. Finally the reconstructed experiments are carried out with ceramic plate. Experimental results show that the proposed method can significantly reduce the highlights area of reconstructed image compared with the highlights area without diffuser. The diffuser can obviously inhibited by highlights, although it can not completely remove the highlights, it plays a very important role in reconstructing specular object with more accurate and better quality.

[1]  Carlo Tomasi,et al.  Full-size projection keyboard for handheld devices , 2003, CACM.

[2]  Yiannis Aloimonos,et al.  Compound eye sensor for 3D ego motion estimation , 2004, 2004 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (IEEE Cat. No.04CH37566).

[3]  Steven A. Shafer,et al.  Using color to separate reflection components , 1985 .

[4]  Ramesh Raskar,et al.  Non-photorealistic camera: depth edge detection and stylized rendering using multi-flash imaging , 2004, SIGGRAPH 2004.

[5]  Stephen Lin,et al.  Highlight removal by illumination-constrained inpainting , 2003, Proceedings Ninth IEEE International Conference on Computer Vision.

[6]  Wu Hai-bin The Review of Structured Light Time Encoding Technologies , 2010 .

[7]  Pieter Peers,et al.  Rapid Acquisition of Specular and Diffuse Normal Maps from Polarized Spherical Gradient Illumination , 2007 .

[8]  David J. Kriegman,et al.  Beyond Lambert: reconstructing specular surfaces using color , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).

[9]  Katsushi Ikeuchi,et al.  Separating reflection components based on chromaticity and noise analysis , 2004, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[10]  In So Kweon,et al.  Voting-based separation of diffuse and specular pixels , 2004 .

[11]  Glen William Brooksby,et al.  Improving 3D surface measurement accuracy on metallic surfaces , 2005, SPIE Optical Metrology.

[12]  Gary M. Bone,et al.  Defect identification on specular machined surfaces , 2013, Machine Vision and Applications.

[13]  Tao Tao,et al.  Specular surface measurement by using a moving diffusive structured light source , 2007, SPIE/COS Photonics Asia.

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