Fuzzy partitions for modelling texture properties: Coarseness, contrast and directionality

The analysis of the perceptual properties of texture plays a fundamental role in tasks like semantic description of images or content-based image retrieval using linguistic queries. In this paper, we propose to model these properties by means of fuzzy partitions defined on the domain of some representative measures. In particular, we have focused our study on the properties of coarseness, contrast and directionality, that play a fundamental role in the human perception of texture. In our approach, the number of fuzzy sets in the partitions, as well as the parameters of the membership functions, are calculated by taking into account the relationship between the computational values given by the measures and the human perception of the corresponding property. The performance of the proposed modelling has been analyzed by applying the obtained fuzzy partitions in several experiments.