Skip to content

Detail of publication


Jiřík, M. and Ryba, T. : Texture Based Segmentation Using Graph Cut and Gabor Filters . Pattern Recognition and Image Analysis, p. 258-261, 2010.


This paper describes a method for texture based segmentation. Texture features are extracted by applying a bank of Gabor filters using two-sided convolution strategy. Probability texture model is represented by Gaussian mixture that is trained with the Expectation-maximization algorithm. Texture similarity, obtained this way, is used like the input of a Graph cut method. We show that the combination of texture analysis and the Graph cut method produce good results.

Detail of publication

Title: Texture Based Segmentation Using Graph Cut and Gabor Filters
Author: Jiřík, M. ; Ryba, T.
Language: English
Date of publication: 1 Jan 2010
Year: 2010
Type of publication: Papers in journals
Title of journal or book: Pattern Recognition and Image Analysis
Page: 258 - 261
/ 2012-01-31 12:54:03 /


Expectation-maximization algorithms, Gabor filter, Gaussian mixtures, Graph cut, Texture analysis, Texture features, Texture models, Texture similarity


 author = {Ji\v{r}\'{i}k, M. and Ryba, T.},
 title = {Texture Based Segmentation Using Graph Cut and Gabor Filters},
 year = {2010},
 journal = {Pattern Recognition and Image Analysis},
 pages = {258-261},
 url = {},