Article ID Journal Published Year Pages File Type
6541143 Computers and Electronics in Agriculture 2013 7 Pages PDF
Abstract
► Automatic classification based on grain features was developed.► Models based on one grain feature gave low classification accuracy.►The morphological and color based models gave mean accuracy of 99%. ► The new algorithm is more efficient than previously developed models.
Keywords
Related Topics
Physical Sciences and Engineering Computer Science Computer Science Applications
Preview
Automatic classification of non-touching cereal grains in digital images using limited morphological and color features
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