NDLI: Application of Rough Set Theory in Coal Gangue Image Process

Content Provider	IEEE Xplore Digital Library
Author	Xian-Min Ma Che Liang
Copyright Year	2009
Abstract	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.
Starting Page	87
Ending Page	90
File Size	354923
Page Count	4
File Format	PDF
ISBN	9780769537443
DOI	10.1109/IAS.2009.102
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-08-18
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Set theory Image edge detection Information systems Belts Knowledge representation Image processing Filtering Water pollution Water resources Information security
Content Type	Text
Resource Type	Article

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