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A new texture descriptor: the Homogeneous Local Binary Pattern (HLBP)

Abstract : This paper presents a simple and novel descriptor named Homogeneous Local Binary Pattern (HLBP) for texture analysis. The purpose of this description is to improve the Local Binary Pattern (LBP) approach basing on the impact of criterion homogeneous region using General Adaptive Neighborhood (GAN) principle. HLBP method is generated by using the criterion homogeneity which helps to represent a significant feature based on relationships between neighboring pixels. The main idea of HLBP is to threshold the distance between the current pixel and each of its neighbors with a homogeneity tolerance value which correspond more to the underlying spatial structures consequently allow extracting highly distinctive invariant features of the image. To assess the performance of the our proposed descriptor, we use "Outex" database and compared with the basic (LBPs). The experimental results show that the proposed Homogeneous Local Binary Pattern gives a good performance in term of classification accuracy.
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Ibtissam Al Saidi, Mohammed Rziza, Johan Debayle. A new texture descriptor: the Homogeneous Local Binary Pattern (HLBP). 9th International Conference, ICISP 2020, Jun 2020, Marrakesh, Morocco. pp.308 à 316, ⟨10.1007/978-3-030-51935-3_33⟩. ⟨emse-02929244⟩



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