%0 Journal Article
%T Computer Vision based Food Grain Classification: a Comprehensive Survey
%A Henry Velesaca
%A Patricia Suarez
%A Raul Mira
%A Angel Sappa
%J Computers and Electronics in Agriculture
%D 2021
%V 187
%F Henry Velesaca2021
%O MSIAU; 600.130; 600.122
%O exported from refbase (http://refbase.cvc.uab.es/show.php?record=3576), last updated on Mon, 31 Jan 2022 12:51:40 +0100
%X This manuscript presents a comprehensive survey on recent computer vision based food grain classification techniques. It includes state-of-the-art approaches intended for different grain varieties. The approaches proposed in the literature are analyzed according to the processing stages considered in the classification pipeline, making it easier to identify common techniques and comparisons. Additionally, the type of images considered by each approach (i.e., images from the: visible, infrared, multispectral, hyperspectral bands) together with the strategy used to generate ground truth data (i.e., real and synthetic images) are reviewed. Finally, conclusions highlighting future needs and challenges are presented.
%U https://doi.org/10.1016/j.compag.2021.106287
%U http://refbase.cvc.uab.es/files/VSM2021.pdf
%P 106287