Texture analysis based on saddle points-based BEMD and LBP

Authors:
JianJia Pan;YuanYan Tang
Affiliations:
Department of Computer Science, Hong Kong Baptist University, Hong Kong SAR, China;Department of Computer Science, Hong Kong Baptist University, Hong Kong SAR, China
Venue:
CAIP'11 Proceedings of the 14th international conference on Computer analysis of images and patterns - Volume Part II
Year:
2011

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Abstract

In this paper, a new texture analysis method(EMDLBP) based on BEMD and LBP is proposed. Bidimensional empirical mode decomposition (BEMD) is a locally adaptive method and suitable for the analysis of nonlinear or nonstationary signals. The texture images can be decomposed to several BIMFs (Bidimensional intrinsic mode functions) by BEMD, which present some new characters of the images. In this paper, firstly, we added the saddle points as supporting points for interpolation to improve the original BEMD, and then the new BEMD method is used to decompose the image to components (BIMFs). After then, the Local Binary Pattern (LBP) method is used to detect the feature from the BIMFs. Experiments shown the texture image recognition rate based on our method is better than other LBP-based methods.