Invariant Texture Segmentation Via Circular Gabor Filters

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16th International Conference on Pattern Recognition (ICPR'02) - Volume 2

Quebec City, QC, Canada

August 11-August 15

ISBN: 0-7695-1695-X

	ASCII Text	x
	Jainguo Zhang, Tieniu Tan, Li Ma, "Invariant Texture Segmentation Via Circular Gabor Filters," Pattern Recognition, International Conference on, vol. 2, pp. 20901, 16th International Conference on Pattern Recognition (ICPR'02) - Volume 2, 2002.

	BibTex	x
	@article{ 10.1109/ICPR.2002.1048450, author = {Jainguo Zhang and Tieniu Tan and Li Ma}, title = {Invariant Texture Segmentation Via Circular Gabor Filters}, journal ={Pattern Recognition, International Conference on}, volume = {2}, year = {2002}, issn = {1051-4651}, pages = {20901}, doi = {http://doi.ieeecomputersociety.org/10.1109/ICPR.2002.1048450}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, }

	RefWorks Procite/RefMan/Endnote	x
	TY - CONF JO - Pattern Recognition, International Conference on TI - Invariant Texture Segmentation Via Circular Gabor Filters SN - 1051-4651 SP EP A1 - Jainguo Zhang, A1 - Tieniu Tan, A1 - Li Ma, PY - 2002 KW - null VL - 2 JA - Pattern Recognition, International Conference on ER -

Jainguo Zhang, Chinese Academy of Sciences

Tieniu Tan, Chinese Academy of Sciences

Li Ma, Chinese Academy of Sciences

DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/ICPR.2002.1048450

In this paper, we focus on invariant texture segmentation, and propose a new method using circular Gabor filters (CGF) for rotation invariant texture segmentation. The traditional Gabor function is modified into a circular symmetric version. The rotation invariant texture features are achieved via the channel output of the CGF. A new scheme of the selection of Gabor parameters is also proposed for texture segmentation. Experiments show the efficacy of this method.

Citation:

Jainguo Zhang, Tieniu Tan, Li Ma, "Invariant Texture Segmentation Via Circular Gabor Filters," icpr, vol. 2, pp.20901, 16th International Conference on Pattern Recognition (ICPR'02) - Volume 2, 2002

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