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http://hdl.handle.net/2080/2325
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DC Field | Value | Language |
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dc.contributor.author | Tripathy, D P | - |
dc.contributor.author | Reddy, R G R | - |
dc.date.accessioned | 2015-05-26T13:22:59Z | - |
dc.date.available | 2015-05-26T13:22:59Z | - |
dc.date.issued | 2015-05 | - |
dc.identifier.citation | 11th Annual International Conference on Information & Computer Science, Athens, Greece,18- 21 May 2015. | en_US |
dc.identifier.uri | http://hdl.handle.net/2080/2325 | - |
dc.description | Copyright belong to proceeding publisher | en_US |
dc.description.abstract | Ore sorting is a useful tool to remove gangue material from the ore and increase the quality of the ore. The vast developments in the area of artificial intelligence allows fast processing of full color digital images for the preferred investigations. In this paper, a novel approach to categorize the ores of iron feed has been proposed based on analyzing colortexture features using two different approaches, based on extensions of the cooccurrence matrix method. In the first method, cooccurrence matrices were computed both between and within the color bands and the second method used joint colortexture features. The dimensions of the image features were reduced by applying Euclidean Distance ranking. A multilayer perceptron neural network model was used as a mapping function to classify the material. | en_US |
dc.language.iso | en | en_US |
dc.publisher | ATINER | en_US |
dc.subject | Novel approach | en_US |
dc.subject | Co-occurrence matrix | en_US |
dc.subject | Gangue separation | en_US |
dc.subject | Iron | en_US |
dc.title | A Novel Approach of CoOccurrence Matrix for Gangue Separation from Iron | en_US |
dc.type | Article | en_US |
Appears in Collections: | Conference Papers |
Files in This Item:
File | Description | Size | Format | |
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document (1).pdf | 1.33 MB | Adobe PDF | View/Open |
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