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.
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Pan, J., Tang, Y. (2011). Texture Analysis Based on Saddle Points-Based BEMD and LBP. In: Real, P., Diaz-Pernil, D., Molina-Abril, H., Berciano, A., Kropatsch, W. (eds) Computer Analysis of Images and Patterns. CAIP 2011. Lecture Notes in Computer Science, vol 6855. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23678-5_60
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DOI: https://doi.org/10.1007/978-3-642-23678-5_60
Publisher Name: Springer, Berlin, Heidelberg
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