EPFL
 Biomedical Imaging GroupSTI
EPFL
  Publications
English only   BIG > Publications > Texture Discrimination


 CONTENTS
 Home Page
 News & Events
 People
 Publications
 Tutorials and Reviews
 Research
 Demos
 Download Algorithms

 DOWNLOAD
 PDF
 Postscript
 All BibTeX References

Texture Discrimination Using Wavelets

M. Unser

Proceedings of the 1993 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'93), New York NY, USA, June 15-17, 1993, pp. 640-641.



A new approach to the characterization of texture properties at multiple scales using an overcomplete wavelet transform is described. It is shown that this representation constitutes a tight frame of l2, and that it has a fast iterative algorithm. A texture is characterized by a set of channel variances estimated at the output of the corresponding filter-bank. Classification experiments with 12 Brodatz textures indicate that the discrete wavelet frame (DWF) approach is superior to a standard (critically sampled) wavelet transform feature extraction. This result also suggests that this approach should perform better than most traditional single resolution techniques (co-occurrences, local linear transform, etc…). A detailed comparison of the classification performance of various orthogonal and biorthogonal wavelet transforms is provided. The DWF feature extraction technique is incorporated into a simple multiple-component texture segmentation algorithm. Some examples are presented.


@INPROCEEDINGS(http://bigwww.epfl.ch/publications/unser9306.html,
AUTHOR="Unser, M.",
TITLE="Texture Discrimination Using Wavelets",
BOOKTITLE="Proceedings of the 1993 {IEEE} Computer Society
        Conference on Computer Vision and Pattern Recognition ({CVPR'93})",
YEAR="1993",
editor="",
volume="",
series="",
pages="640--641",
address="New York NY, USA",
month="June 15-17,",
organization="",
publisher="",
note="")

© 1993 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from IEEE.
This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.