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Research on recognition of coal and gangue based on image processing

Research on recognition of coal and gangue based on image processing In order to avoid the waste of water resources and environmental pollution caused by separating coal and gangue in the traditional methods, a novel method based on image processing is proposed in this paper. Firstly the image of coal or gangue is preprocessed. Then the mean value of gray histogram is extracted which serves as the statistical feature value to initially recognize coal and gangue. Then the textural feature is extracted from the image which is based on an adaptive window of texture analysis. The adaptive window size is determined by the contrast texture feature parameter. The adaptive window of texture analysis can improve the discriminability of coal and gangue. This method not only considers the image’s gray feature but also utilizes the image’s spatial information, so the recognition precision is improved. This method provides new ideas for dry separation technology. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png World Journal of Engineering Emerald Publishing

Research on recognition of coal and gangue based on image processing

World Journal of Engineering , Volume 12 (3): 8 – Aug 1, 2015

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References (11)

Publisher
Emerald Publishing
Copyright
Copyright © Emerald Group Publishing Limited
ISSN
1708-5284
DOI
10.1260/1708-5284.12.3.247
Publisher site
See Article on Publisher Site

Abstract

In order to avoid the waste of water resources and environmental pollution caused by separating coal and gangue in the traditional methods, a novel method based on image processing is proposed in this paper. Firstly the image of coal or gangue is preprocessed. Then the mean value of gray histogram is extracted which serves as the statistical feature value to initially recognize coal and gangue. Then the textural feature is extracted from the image which is based on an adaptive window of texture analysis. The adaptive window size is determined by the contrast texture feature parameter. The adaptive window of texture analysis can improve the discriminability of coal and gangue. This method not only considers the image’s gray feature but also utilizes the image’s spatial information, so the recognition precision is improved. This method provides new ideas for dry separation technology.

Journal

World Journal of EngineeringEmerald Publishing

Published: Aug 1, 2015

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