Gradient Color Tensor based Approach for Spectral Matting

Adam Ghorbel, Marwen Nouri, Emmanuel Marilly

2013

Abstract

Image matting aims to extract foreground objects from a given image in a fuzzy mode. One of the major state-of-the-art methods in this field is spectral matting. It automatically computes fuzzy matting components by using the smallest eigenvectors of a defined Laplacian matrix that is generated from affinities computation between adjacent pixels in an image. Results obtained by such approach are coarsely related to the ability of defining an affinity matrix that it should be able to well separate between different pixels’ clusters. To accomplish better matting and get better results, we propose a new spectral matting approach. We use a color tensor gradient of color images in order to enhance the affinity computation process.

References

  1. Porter, T, Duff, T, 1984.Compositing Digital Images. In: Proceedings of ACM SIGGRAPH.
  2. Wang, J, Cohen, M. F., 2007. Image and Video Matting: A survey. Foundations and trends in computer Graphics and vision.
  3. Ruzon M, Tomasi C, 2000. Alpha estimation in natural images. In CVPR.
  4. Y.-Y Chuang, B.Curless, D.H.salesin, szeliski, 2001. A Bayesian approach to digital matting. IEEE CVPR.
  5. J. Sun, J. Jia, C.-K. Tang, H.-Y. Shum,2004. Poisson matting. In Proceedings of ACM SIGGRAPH.
  6. L. Grady, T. Schiwietz, S. Aharon, R. Westermann, 2005. Random walks for interactive alpha-matting. In Proceedings of VIIP 2005.
  7. X. Bai and G. Sapiro, 2007. A geodesic framework for fast interactive image and video segmentation and matting. In Proceedings of IEEE ICCV.
  8. A. Levin, D. Lischinski, and Y. Weiss, 2006. A closed form solution to natural image matting. In Proceedings of IEEE CVPR.
  9. A. Levin, A. Rav-Acha A., D. Lischinski, 2008. Spectral matting. IEEE transactions on pattern analysis and machine intelligence, 30(10), pp.1699-712.
  10. Jun Zhu, Dengsheng Zhang, Guojun Lu, 2010. An Enhancement to close form method for natural image matting. Digital image computing: Techniques and Applications.
  11. Yu, S. X, Shi, J, 2003. Multiclass spectral clustering. In Proceedings of international Conference on Computer Vision.
  12. Wu-Chih Hu, Deng-Yuan Huang, Ching-Yu Yang, Jia-Jie Jhu, Cheng-Pin, 2010. Automatic and accurate Image matting. In: Proceedings of the 2nd international Conference on Computational Collective IntelligenceTechnology and Applications.
  13. Wu-Chih Hu, and Jung-Fu-Hsu, 2012. Automatic image matting using component-Hue-Difference-Based Spectral Matting. In: Proceedings of ACIIDS'12 of the 4th Asian Conference on Intelligent Information and Database Systems, Berlin, Heidelburg.
  14. Tung-Yu Wu, hung-hui juan, Horng-Shing Lu, 2012. Improved spectral matting by iterative k-means clustering and the modularity measure. IEEE International Conference an Acoustics, Speech, and Signal Processing, Kyoto international conference center, Japan.
  15. Silvano Di Zenzo, 1986: A note on the gradient of a multiimage. Computer Vision, Graphics and Image processing.
Download


Paper Citation


in Harvard Style

Ghorbel A., Nouri M. and Marilly E. (2013). Gradient Color Tensor based Approach for Spectral Matting . In Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2013) ISBN 978-989-8565-47-1, pages 426-430. DOI: 10.5220/0004215404260430


in Bibtex Style

@conference{visapp13,
author={Adam Ghorbel and Marwen Nouri and Emmanuel Marilly},
title={Gradient Color Tensor based Approach for Spectral Matting},
booktitle={Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2013)},
year={2013},
pages={426-430},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004215404260430},
isbn={978-989-8565-47-1},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2013)
TI - Gradient Color Tensor based Approach for Spectral Matting
SN - 978-989-8565-47-1
AU - Ghorbel A.
AU - Nouri M.
AU - Marilly E.
PY - 2013
SP - 426
EP - 430
DO - 10.5220/0004215404260430