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Identifying rice grains using image analysis and sparse-representation-based classification

Identifying rice grains using image analysis and sparse-representation-based classification

Starting at: Rs.5,500.00

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Identifying rice grains using image analysis and sparse-representation-based classification

Rice ( Oryza sativa L.) is a major staple food worldwide, and is traded extensively. The objective of this study is to distinguish the rice grains of 30 varieties nondestructively using image processing and sparse-re presentation-based classification (SRC). SRC uses over-compl ete bases to capture the represe ntative traits of rice grains. In the experiments, rice grain images were acquire d by microscopy.The morphological, color, and textural traits of the grain body, sterile lemmas, and brush were quantified.An SRC classifier was subsequently developed to identify the varieties of the grains using the traits as the inputs. The proposed approach could discriminate rice grain varieties with an accuracy of 89.1%.


 


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  • Model: PROJ7547
  • 999 Units in Stock
  • Manufactured by: ClickMyProjects

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This product was added to our catalog on Saturday 29 July, 2017.

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