Monogenic-LBP: A New Approach for Rotation Invariant Texture Classification

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Authors Lin Zhang, Lei Zhang, Zhenhua Guo, and David Zhang
Journal/Conference Name 2010 IEEE International Conference on Image Processing (ICIP 2010)
Paper Category
Paper Abstract Analysis of two-dimensional textures has many potential applications in computer vision. In this paper, we investigate the problem of rotation invariant texture classification, and propose a novel texture feature extractor, namely Monogenic-LBP (M-LBP). M-LBP integrates the traditional Local Binary Pattern (LBP) operator with the other two rotation invariant measures: the local phase and the local surface type computed by the 1st-order and 2nd-order Riesz transforms, respectively. The classification is based on the image’s histogram of M-LBP responses. Extensive experiments conducted on the CUReT database demonstrate the overall superiority of M-LBP over the other state-of-the-art methods evaluated.
Date of publication 2010
Code Programming Language MATLAB

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