Application of Rough Set Theory in Coal Gangue Image Process

A novel application of rough Net theory M the coal gangue image process is introduced hi this paper. Based on rough Net theory, the coal gangue image process strategy is proposed to select the coal gangues out from coal bulks on the coal bell transporter. The rough set knowledge representation theory are described., and the coal gangue image processing operations such as the denoising, enhancement, sharpening and edge detection by, the rough set theory are analyzed. Furthermore, the rough set filtering result is compared with the median, filtering, result, and various edge defection methods are also compared with the proposed edge defection, method based on rough set. The compared results demonstrate that the coal gangue image process method based on rough set outperforms the other methods. It can be concluded from the comparisons that the coal gangues can be detected out from coal mass by rough set theory strategy, therefore the proposed method is effective for selection and classification the coal gangues.