Illumination invariant unsupervised segmenter

Proceedings - International Conference on Image Processing, ICIP

Volumn , Issue , 2009, Pages 4025-4028

  Haindl, Michal ^a   Mikeš, Stanislav ^a   Vácha, Pavel ^a  

^a INSTITUTE OF INFORMATION THEORY AND AUTOMATION   (Czech Republic)

Author keywords

Illumination invariance; Unsupervised image segmentation

Indexed keywords

DIGITAL IMAGE STORAGE; IMAGING SYSTEMS; MARKOV PROCESSES; TEXTURES;

GAUSSIAN MIXTURE MODEL; ILLUMINATION INVARIANCE; ILLUMINATION INVARIANT; INITIAL ESTIMATION; MARKOVIAN MODEL; MULTI-SPECTRAL; MULTISPECTRAL TEXTURE SEGMENTATION; MULTISPECTRAL TEXTURES; OPTIMAL NUMBER; PARAMETRIC SPACES; SEGMENTATION ALGORITHMS; SEGMENTATION METHODS; SEGMENTER; TEXTURE SEGMENTS; UNSUPERVISED IMAGE SEGMENTATION;

IMAGE SEGMENTATION;

EID: 77951973877     PISSN: 15224880     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICIP.2009.5413753     Document Type: Conference Paper

References (13)

1. Todd R. Reed and J. M. Hans du Buf, "A review of recent texture segmentation and feature extraction techniques," CVGIP-Image Understanding, vol. 57, no. 3, pp. 359-372, May 1993.
2. R.L. Kashyap, "Image models," in Handbook of Pattern Recognition and Image Processing, K.S. Fu T.Y. Young, Ed. Academic Press, New York, 1986.
3. M. Haindl, "Texture synthesis," CWI Quarterly, vol. 4, no. 4, pp. 305-331, December 1991.
4. D.K. Panjwani and G. Healey, "Markov random field models for unsupervised segmentation of textured color images," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 17, no. 10, pp. 939-954, 1995.
5. B.S. Manjunath and R. Chellapa, "Unsupervised texture segmentation using markov random field models," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 13, pp. 478-482, 1991. (Pubitemid 21676522)
6. P. Andrey and P. Tarroux, "Unsupervised segmentation of markov random field modeled textured images using selectionist relaxation," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 20, no. 3, pp. 252-262, March 1998.
7. Michal Haindl, "Texture segmentation using recursive markov random field parameter estimation," in Proceedings of the 11th SCIA, Lyngby, Denmark, June 1999, pp. 771-776, Pattern Recognition Society of Denmark.
8. M. Haindl and S. Mikeš, "Model-based texture segmentation," Lecture Notes in Computer Science, , no. 3212, pp. 306-313, 2004.
9. M. Haindl and S. Šimberová, Theory & Applications of Image Analysis, chapter A Multispectral Image Line Reconstruction Method, pp. 306-315, World Scientific Publishing Co., Singapore, 1992.
10. Pavel Vacha and Michal Haindl, "Image retrieval measures based on illumination invariant textural mrf features," in CIVR '07: Proceedings of the 6th ACM international conference on Image and video retrieval, New York, NY, USA, 2007, pp. 448-454, ACM Press.
11. M. Haindl and S. Mikeš, "Texture segmentation benchmark," in Proceedings of the 19th International Conference on Pattern Recognition, ICPR 2008, Los Alamitos, December 2008, pp. 1-4, IEEE Computer Society.
12. M. Haindl and S. Mikeš, "Unsupervised texture segmentation using multispectral modelling approach," in Proceedings of the 18th International Conference on Pattern Recognition, ICPR 2006, Los Alamitos, August 2006, vol. II, pp. 203-206, IEEE Computer Society.
13. Minh A. Hoang, Jan-Mark Geusebroek, and Arnold W.M. Smeulders, "Color texture measurement and segmentation," Signal Processing, vol. 85, no. 2, pp. 265-275, 2005.