Decoding of Color Coded Structured Light Using a New Color Feature

Article Preview

Abstract:

In this paper, color coded structured light based on pseudo-random sequence is adopted, and a new decoding method is proposed. It includes three steps. First, the stripe centers are extracted through the use of peak detection. Second, the stripe colors are identified using k-means clustering algorithm on a new color feature with high discriminating power. This feature is related to the spectral sensitivity of red, green and blue sensors, the direction of the illumination source, the normal and albedo of the surface, and the spectral power distribution of the incident light, but it is insensitive to the intensity. Finally, a four-step matching method is presented in sequence matching, which is aim to match the subsequences with the length less than the window size. The experimental results show that our proposed decoding method has advantage of high accuracy.

You might also be interested in these eBooks

Info:

Periodical:

Pages:

229-236

Citation:

Online since:

October 2014

Export:

Price:

Permissions CCC:

Permissions PLS:

Сopyright:

© 2014 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

* - Corresponding Author

[1] C. Han, M. Li, and C. Zhang and H. Yang. Color classification for structured light of De Bruijn based on clustering analysis. Recent Advances in Computer Science and Information Engineering. Springer Berlin Heidelberg. 2012: 359-364.

DOI: 10.1007/978-3-642-25792-6_54

Google Scholar

[2] P. Fechteler and P. Eisert. Adaptive colour classification for structured light systems. Computer Vision, IET. 2009, 3(2): 49-59.

DOI: 10.1049/iet-cvi.2008.0058

Google Scholar

[3] P. Fechteler, P. Eisert and J. Rurainsky. Fast and high resolution 3d face scanning. IEEE International Conference on Image Processing (ICIP), (2007).

DOI: 10.1109/icip.2007.4379251

Google Scholar

[4] L. Zhang, B. Curless and S. Seitz. Rapid shape acquisition using color structured light and multi-pass dynamic programming. Proceedings of the First International Symposium on 3D Data Processing Visualization and Transmission. (2002).

DOI: 10.1109/tdpvt.2002.1024035

Google Scholar

[5] O. Ulusoy, F. Calakli and G. Taubin. Robust one-shot 3D scanning using loopy belief propagation. IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops (CVPRW). (2010).

DOI: 10.1109/cvprw.2010.5543556

Google Scholar

[6] X. Zhang and L. Zhu. Determination of edge correspondence using color codes for one-shot shape acquisition. Optics and Lasers in Engineering. 2011, 49(1): 97-103.

DOI: 10.1016/j.optlaseng.2010.08.013

Google Scholar

[7] D. Caspi, N. Kiryati and J. Shamir. Range imaging with adaptive color structured light. IEEE Transactions on Pattern Analysis and Machine Intelligence. 1998, 20(5): 470-480.

DOI: 10.1109/34.682177

Google Scholar

[8] Q. Jia, B. Wang and X. Luo. Extraction of central positions of light stripe in sub-pixel in 3D surface measurement based on light sectioning method. Optics and Precision Engineering. 2010, 18(2): 390-396.

Google Scholar

[9] S. Shafer. Using color to separate reflection components. Color Research & Application. 1985, 10(4): 210-218.

DOI: 10.1002/col.5080100409

Google Scholar

[10] R. Morano, C Ozturk, R Conn, S. Dubin and J. Nissanov. Structured light using pseudorandom codes. IEEE Transactions on Pattern Analysis and Machine Intelligence. 1998, 20(3): 322-327.

DOI: 10.1109/34.667888

Google Scholar

[11] X. Zhang, L. Zhu, and L. Chu, Evaluation of coded structured light methods using ground truth., IEEE 5th International Conference on Cybernetics and Intelligent Systems (CIS), (2011).

DOI: 10.1109/iccis.2011.6070312

Google Scholar

[12] B. Curless and M. Levoy. Better optical triangulation through spacetime analysis. Proceedings of the Fifth International Conference on Computer Vision. (1995).

DOI: 10.1109/iccv.1995.466772

Google Scholar

[13] T. Gevers and A. Smeulders. Color-based object recognition. Pattern recognition. 1999, 32(3): 453-464.

DOI: 10.1016/s0031-3203(98)00036-3

Google Scholar

[14] H. D. Cheng, X. H. Jiang, Y. Sun and J. Wang. Color image segmentation: advances and prospects. Pattern recognition. 2001, 34(12): 2259-2281.

DOI: 10.1016/s0031-3203(00)00149-7

Google Scholar

[15] J. M. Geusebroek, R. V. D. Boomgaard, A. V. M. Smeulders and H. Geerts. Color invariance. IEEE Transactions on Pattern Analysis and Machine Intelligence. 2001, 23(12): 1338-1350.

DOI: 10.1109/34.977559

Google Scholar

[16] C. Garcia and G. Tziritas. Face detection using quantized skin color regions merging and wavelet packet analysis. IEEE Transactions on Multimedia. 1999, 1(3): 264-277.

DOI: 10.1109/6046.784465

Google Scholar