Tuesday, July 5, 2016

Classification of Grain Based On the Morphology, Color and Texture Information Extracted From Digital Images

Brazil is one of the largest grain producers in the world and grain classification are of great importance to the industry, since they are related to quality and economic factors. The objective of this study was to use methods of data analysis of shape, color and  texture extracted from  digital images for grain classification. From the results obtained it was demonstrated that  the  use of  patterns of  morphology, color  and  texture  extracted from images using  the  digital imaging processing techniques are effective for grain classification. The LBP texture pattern proved the most efficient information among the three, and with it alone was possible to reach a 94% hit rate. Combining addition to the pattern shape of LBP information with FCC and color with HSV was possible to improve the success rate to 96%.

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