TY  - JOUR
AU  - Henry Velesaca
AU  - Patricia Suarez
AU  - Raul Mira
AU  - Angel Sappa
PY  - 2021//
TI  - Computer Vision based Food Grain Classification: a Comprehensive Survey
T2  - CEA
JO  - Computers and Electronics in Agriculture
SP  - 106287
VL  - 187
N2  - 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.
UR  - https://doi.org/10.1016/j.compag.2021.106287
L1  - http://refbase.cvc.uab.es/files/VSM2021.pdf
N1  - MSIAU; 600.130; 600.122
ID  - Henry Velesaca2021
ER  -