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Color texture image classification based on fractal features and extreme learning machine

Texture classication, especially color texture classication, is considered a signicant step in segmentation and object classication. The property of color and texture is important for characterizing objects in natural scenes. Fractal dimension (FD) has many applications in theeld of image compression and image segmentation. A series of FD features, such as mean, standard deviation, lacunarity, kurtosis, skewness, entropy, inverse difference moment, contrast, energy, dissimilarity, homogeneity, and maximum probability, are investigated for obtaining the maximum discrimination. In this manuscript, a methodology is proposed that is based on FD and an extreme learning machine for color texture classication. Performance of the proposed methodology is evaluated by comprehensive experiments on a publicly available data set. The experiments show that the proposed methodology has advantages over other color texture analysis methods.