PT Journal
AU Henry Velesaca
   Patricia Suarez
   Raul Mira
   Angel Sappa
TI Computer Vision based Food Grain Classification: a Comprehensive Survey
SO Computers and Electronics in Agriculture
JI CEA
PY 2021
BP 106287
VL 187
AB 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.
ER