Application of Rough Set Theory in Coal Gangue Image Process

A novel application of rough set theory in the coal gangue image process is introduced in this paper. Based on rough set theory, the coal gangue image process strategy is proposed to select the coal gangues out from coal bulks on the coal belt 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 detection methods are also compared with the proposed edge detection 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.