A TV Flow Based Local Scale Measure for Texture Discrimination

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 3022, Issue , 2004, Pages 578-590

  Brox, Thomas ^a   Weickert, Joachim ^a  

^a SAARLAND UNIVERSITY   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTER VISION;

IMAGE INTENSITIES; REGION-BASED; SECOND MOMENTS; SPARSE FEATURES; SPECIAL PROPERTIES; TEXTURE DISCRIMINATION; TEXTURE FEATURES; TEXTURE SEGMENTATION;

IMAGE SEGMENTATION;

EID: 35048850551     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-24671-8_46     Document Type: Article

References (21)

1. F. Andreu, C. Ballester, V. Caselles, and J. M. Mazón. Minimizing total variation flow. Differential and Integral Equations, 14(3):321-360, Mar. 2001.
2. J. Bigiin, G. H. Granlund, and J. Wiklund. Multidimensional orientation estimation with applications to texture analysis and optical flow. IEEE Transactions on Pattern Analysis and Machine Intelligence, 13(8):775-790, Aug. 1991.
3. P. Brodatz. Textures: a Photographic Album for Artists and Designers. Dover, New York, 1966.
4. T. Brox, M. Welk, G. Steidl, and J. Weickert. Equivalence results for TV diffusion and TV regularisation. In L. D. Griffin and M. Lillholm, editors, Scale-Space Methods in Computer Vision, volume 2695 of Lecture Notes in Computer Science, pages 86-100. Springer, Berlin, June 2003.
5. J. H. Elder and S. W. Zucker. Local scale control for edge detection and blur estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence, 20(7):699-716, July 1998.
6. W. Förstner and E. Gulch. A fast operator for detection and precise location of distinct points, corners and centres of circular features. In Proc. 1SPRS Intercommission Conference on Fast Processing of Photogrammetric Data, pages 281-305, Interlaken, Switzerland, June 1987.
7. D. Gabor. Theory of communication. Journal IEEE, 93:429-459,1946.
8. M. Galun, E. Sharon, R. Basri, and A. Brandt. Texture segmentation by multiscale aggregation of filter responses and shape elements. In Proc. IEEE International Conference on Computer Vision, Nice, France, Oct. 2003. To appear.
9. G. Cornez, J. L. Marroquín, and L. E. Sucar. Probabilistic estimation of local scale. In Proc. International Conference on Pattern Recognition, volume 3, pages 798-801, Barcelona, Spain, Sept. 2000.
10. H. Jeong and I. Kim. Adaptive determination of filter scales for edge detection. IEEE Transactions on Pattern Analysis and Machine Intelligence, 14(5):579-585, May 1992.
11. T. Lindeberg. Scale-Space Theory in Computer Vision. Kluwer, Boston, 1994.
12. T. Lindeberg. Principles for automatic scale selection. In B. Jähne, H. Haußecker, and P. Geißler, editors, Handbook on Computer Vision and Applications, volume 2, pages 239274. Academic Press, Boston, USA, 1999.
13. S. Marcelja. Mathematical description of the response of simple cortical cells. Journal of Optical Society of America, 70:1297-1300,1980.
14. B. A. Olshausen and D. J. Field. Sparse coding with an over-complete basis set: A strategy employed by VI? Vision Research, 37:3311-3325,1997.
15. A. R. Rao and B. G. Schunck. Computing oriented texture fields. CVGIP: Graphical Models and Image Processing, 53:157-185,1991.
16. T. R. Reed and J. M. H. du Buf. A review of recent texture segmentation and feature extraction techniques. Computer Vision, Graphics and Image Processing, 57(3):359-372, May 1993.
17. M. Rousson.T. Brox, and R. Deriche. Active unsupervised texture segmentation on a diffusion based feature space. In Proc. 2003 IEEE Computer Society Conf. on Computer Vision and Pattern Recognition, volume 2, pages 699-704, Madison, WI, June 2003. IEEE Computer Society Press.
18. L. I. Rudin, S. Osher.and E. Fatemi. Nonlinear total variation based noise removal algorithms. Physica D, 60:259-268,1992.
19. J. Sporring, C. I. Colios, and P. E. Trahanias. Generalized scale-selection. Technical Report 264, Foundation for Research and Technology - Hellas, Crete, Greece, Dec. 1999.
20. J. Weickert, B. M. ter Haar Romeny, and M. A. Viergever. Efficient and reliable schemes for nonlinear diffusion filtering. IEEE Transactions on Image Processing, 7(3):398-10, Mar. 1998.
21. S.-C. Zhu, C. Guo, Y. Wu, and W. Wang. What are textons? In A. Heyden, G. Sparr, M. NIelsen, and P. Johansen, editors, Proc. 7th European Conference on Computer Vision, volume 2353 of Lecture Notes in Computer Science, pages 793-807, Copenhagen, Denmark, May 2002. Springer.