Discrimination analysis of coal and gangue using multifractal properties of optical texture

The separation of coal and gangue is an important part in the coal-preparation process, which can be realized by image recognition technique. The unique optical texture of coal is the most obvious visual features to distinguish coal and gangue. The current research represented the attempt to implement the multifractal analysis in the optical texture of coal and gangue. Firstly, fractal theory is applied to verify the multiscale characteristics of coal and gangue images. Then a new method of using the multifractal spectrum to describe and identify the optical texture characteristics of coal and gangue is constructed. Finally, we analyzed the coal and gangue images according to the physical meaning of the parameters in the multifractal spectrum. The results demonstrate that the optical texture of coal and gangue presents the characteristics of complexity and self-similarity, and the multifractal spectrum is an appropriate tool for characterizing the optical texture structure of the coal and gangue. The representative parameters in multifractal spectrum can be used as efficient features for the recognition of coal and gangue. It is thus clear that the multifractal model is a novel and feasible method to describe and recognize the optical texture characteristics of coal and gangue images.

Automated summary

The optical texture of coal and gangue can be described and recognized using multi-scale fractal analysis, and the parameters in the multifractal spectrum can serve as efficient features for recognition. This is a novel and feasible method.