Abstract
Local Binary Patterns (LBP) is a local approach widely used in the field of texture analysis. Generally, the LBP algorithm is applied on the original texture. Our contribution, as presented in this paper, will be to apply this algorithm on the sub bands resulting from the wavelet transform. This allows characterising texture on various resolution levels. As training bases, we used a set of 30 elements extracted from the Brodatz album and a set of 40 elements extracted from the Vistex album. To test the invariance of the proposed method, several tests have been carried out on textures with rotation changes or scale changes, and many parameters have been tested including the radius of the LBP, the distance measure and the wavelet's nature. These results demonstrate the effectiveness of our characterization method in texture image classification experiments.
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